#barcode recognition mode improved

[industrynewsupdates]

Image Recognition Market Size, Share And Trends Analysis Report

The global image recognition market size is expected to reach USD 128.3 billion by 2030, registering a CAGR of 12.8% from 2024 to 2030, according to a new report by Grand View Research, Inc. Image processing and recognition have evolved with numerous powerful applications, such as security and surveillance, and medical imaging that have created a great value from a business perspective. Functions of figure identification, such as facial or object recognition, visual geolocation, barcode reading, and automated driver assistance, among other industrial automation-related functions, have demonstrated the versatility of this technology. When combined with AI, this technology has begun to create valuable growth opportunities in several verticals, such as gaming, social networking, and e-commerce. For instance, Twitter and Facebook, two major platforms in the world of social networking, have benefited from the technology in terms of audience engagement as they have created a more connected experience by encouraging users to share images and tag their friends.

The advent of digital cameras, particularly cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of images and videos. A vast amount of visual and digital data is being captured and shared through several applications, websites, social networks, and other digital channels. Several businesses have leveraged this online content to deliver better and smarter services to their customers, with the use of digital image processing. For instance, in October 2019, SnapPay Inc., a U.S. based payment platform provider, has launched facial recognition payment technology in the North America region. By using this thechnology in its payment solution, the company has aimed at allowing its customers a new level of convenience for payments at retail outlets.

Gather more insights about the market drivers, restrains and growth of the Image Recognition Market

Image Recognition Market Report Highlights

• Facial recognition dominated the market and accounted for the largest revenue share of 22.5% in 2023. The increasing demand for enhanced security measures across various industries, such as government, banking, and retail, has significantly contributed to the dominance of facial recognition systems.

• The service segment led the market and accounted for the largest revenue share of 39.1% in 2023. The service segment offers tailored image recognition solutions that can be customized to meet the specific needs of businesses across various industries.

• The cloud segment held the largest market revenue share of 71.6% in 2023. The rise in the cloud-based market is due to its greater use in industries needing centralized monitoring, such as BFSI, media, government, and entertainment.

• The retail & e-commerce segment dominated the market with a share of 21.0% in 2023. E-commerce websites prioritize content management to enhance their product offerings and boost sales.

• The marketing & advertising segment held the largest market share of 29.6% in 2023. Many businesses adopted technology with advanced advertising, customer interaction, and branding to improve their marketing activities.

• North America image recognition market dominated the global market and accounted for the largest revenue share of 34.0% in 2023. The rise in the market is due to the growing inclusion of AI and mobile computing in online shopping and e-commerce industries.

Image Recognition Market Segmentation

Grand View Research has segmented global image recognition market report based on, technique, component, deployment mode, vertical, application, and region:

Image Recognition Technique Outlook (Revenue, USD Million, 2018 - 2030)

• QR/ Barcode Recognition

• Object Recognition

• Facial Recognition

• Pattern Recognition

• Optical Character Recognition

Image Recognition Component Outlook (Revenue, USD Million, 2018 - 2030)

• Hardware

• Software

• Service

o Managed

o Professional

o Training, Support, and Maintenance

Image Recognition Deployment Mode Outlook (Revenue, USD Million, 2018 - 2030)

• Cloud

• On-Premises

Image Recognition Vertical Outlook (Revenue, USD Million, 2018 - 2030)

• Retail & E-commerce

• Media & Entertainment

• BFSI

• Automobile & Transportation

• Telecom & IT

• Government

• Healthcare

• Others

Image Recognition Application Outlook (Revenue, USD Million, 2018 - 2030)

• Augmented Reality

• Scanning & Imaging

• Security & Surveillance

• Marketing & Advertising

• Image Search

Image Recognition Regional Outlook (Revenue, USD Million, 2018 - 2030)

• North America

o U.S.

o Canada

o Mexico

• Europe

o UK

o Germany

o France

• Asia Pacific

o China

o India

o Japan

o Australia

o South Korea

• Latin America

o Brazil

• Middle East and Africa (MEA)

o Saudi Arabia

o South Africa

o UAE

Order a free sample PDF of the Image Recognition Market Intelligence Study, published by Grand View Research.

[file-formats-programming]

Generate DataMatix Barcode with C40 & Text Encoding Scheme inside .NET Apps

What's New in this Release?

The latest version of Aspose.BarCode for .NET 17.5.0 has been released. The major development in this release is the support for functionality to generate DataMatix barcode with C40 and Text encoding scheme. Functionality of AllSupportedTypes recognition mode has also been improved and incorporated in this release. It provides the most convenient way to produce C40 encoded DataMatrix. Aspose.BarCode for .NET provides the functionality to generate the DataMatrix barcode with Text encoding scheme. Code snippet on the blog announcement page demonstrates how to create DataMatrix with Text mode enabled.  This month’s release also includes few bug fixes that were reported by Aspose customers in the previous release, such as functionality of AllSupportedTypes recognition mode has been improved, functionality to read barocde from PDF file has been improved and functionality to recognize DataMatix barcode has been improved. Recognistion algorithm has been improved in much a way that it is now capable of decoding nonprintable chars and decoding some special characters/symbols. Below is the list of new and improved features supported in this version.

Add support for generate DataMatrix with Text encodation scheme

Add support for generate DataMatrix with C40 encodation scheme

Unable to get the supplement code text from EAN13 coded barcode (supplement barcode is bit blurred)

Aspose.BarCode is not producing correct output after reading UPCA barcode

Different recognition result with DecodeType.AllSupportedTypes and BarCodeReadType.AllSupportedTypes

Aspose.BarCode is unable to extract barcode from PDF

Aspose Barcode is not reading DataMatrix coded barcode correctly

Newly added documentation pages and articles

Some new tips and articles have now been added into Aspose.BarCode for .NET documentation that may guide users briefly how to use Aspose.BarCode for performing different tasks like the followings.

Create C40 Encoded Datamatrix Barcode

Create Text Encoded Datamatrix Barcode

Overview: Aspose.BarCode for .NET

Aspose.BarCode is a .NET component for generation and recognition of Linear and 2D barcodes on all kinds of .NET applications. It supports WPF with 29+ Barcode symbologies like OneCode, QR, Aztec, MSI, EAN128, EAN14, SSCC18, Code128, Code39, Postnet, MarcoPDF417, Datamatrix, UPCA etc. Other features include barcode insertion in PDF, Word and Excel documents. Also take image output in BMP, GIF, JPEG, PNG and WMF formats. You can also control image styles such as background color, bar color etc.

More about Aspose.Report for .NET

Homepage of C# & VB.NET Barcode Component Aspose.BarCode for .NET

Download of Aspose.BarCode for .NET

Online documentation of Aspose.BarCode for .NET

[wamatechblog]

Top 8 Libraries for React Native UI Components

The following are the top UI Component libraries for developing React Native apps:

React Native Maps is one

Native React Maps

Just use React Native Maps if you want to explore maps more. This package offers specific map components for iOS and Android. Developers are free to adjust the markers, the map view region, the map style, and other elements that can be overlaid on a map.

You may improve the user experience by using an animated API to even animate your map’s zoom and placement.

NativeBase 2.

NativeBase

NativeBase is an excellent place for beginning React Native developers to start building apps. A teaching app, a Twitter clone app, and a Native starting app are some of the open-source creations of this toolkit. A premium beginning package is also available from this library.

NativeBase, a well-known UI component package, is well-known for providing mobile-first and accessible features. You may build and maintain a reliable design framework using this library for both online and mobile platforms. Additionally, it offers a specific collection of components for creating React Native UI.

React Native ARIA and themeable design frameworks that are optimised for both dark and light modes are additional accessibility features supported by this UI component library.

NativeBase is the best option if you require toast for elements, sophisticated elements like row, skeleton, and column for layout, coupled with crucial elements like icons, overlays, flex, checkboxes, and buttons. NativeBase, a tool for developers to create personalised UI components, is driven by Styled System.

3. Native React Components

Native React Elements

This is a cross-platform UI component library that is easy to customise and has various contributed parts. Customized themes are supported. Additionally, it has components like overlays, dividers, social symbol buttons, avatars, pricing, badges, and star ratings.

React Native Elements’ primary goal is to give developers with a ready-made kit with a reliable API and appealing look and feel, but it also aims to provide an all-inclusive UI kit for building React Native apps.

4. Native React Camera

React Native Camera, often known as RN Camera, is an excellent library that facilitates camera communication on your smartphone. It enables programmers to utilise a few simple functions without having to worry about native code.

For both Android and iOS, the camera component of React Native supports barcode scanning, facial recognition, photos, text recognition, and videos.

Also read: Mobile App Development Company in Kolkata

 5. Native React Paper

This open-source, cross-platform toolkit offers more than 30 production-ready, resizable elements that adhere to the Material Design guidelines. Both dark and bright themes are fully supported. Additionally, it makes switching between several themes easy.

Simply use React Native’s Appearance API to apply theme moving based on device settings if you have customised the theme. In order to ensure that the remaining MVP is in place, Paper also helps you to quickly add simple, straightforward, and easily adaptable UI components to your development.

6. Bit for Native of React

The Bit is a fantastic tool for building component-driven programmes even if it is not a library. Systems that are simpler to comprehend, construct more quickly, collaborate on, investigate, and manage can benefit from this flexible toolchain.

You may use Bit in your project to monitor items and export them to Bit.dev, the company’s virtual monorepo. This makes every component available and useable for further projects. They are individually created and maintained by developers.

They are able to create as many applications as they require. They can also change the operation of programmes by removing or adding certain components. With Bit, they can make modifications without having to set up a development environment.

7. Native Gifted Chat React

Native Gifted Chat React

For your React Native project, are you looking for a full chat UI library? Simply choose React Native Gifted Chat after that. Numerous applications already include a well-known chat feature. This feature or capability is made simpler to use with React Native Gifted Chat. Redux is also supported by this library.

This library provides a variety of customizable elements. TypeScript is used for all of the components. These aspects include the ability to click on links, copy messages to the clipboard, load earlier messages, use multiple text input fields, attach files, create profile avatars, and enhance bot capabilities.

8. Native React Snap Carousel

Snap Carousel in React Native

There are numerous ways to display a number of photographs in a gallery view using React Native. A well-known method to achieve the same result is the carousel. Multiple layouts, product previews, effective administration of a large number of items, parallax graphics, and other features are included.

Both iOS and Android are compatible with Carousel. It makes it easier for the user to scroll through a set of pictures that may be shown both vertically and horizontally. Simply put, it enables developers to display their information on various mobile devices.

Choose React Native Snap Carousel for adding attractive sliders or carousels to your application. This UI library has a lot of recommendations for improving efficiency; it is well-documented and has a few other helpful features as well.

A comprehensive API with property and several plug-and-use layout patterns is available in Snap Carousel. Additionally, it gives developers the ability to implement animations and personalised interpolations.

Also read: Mobile App Development Company in Bangalore

[mhsn033]

Google Lookout: App reads grocery labels for blind people

Image copyright Google

Google’s AI can now name meals within the grocery store, in a transfer designed to assist the visually impaired.

It’s segment of Google’s Lookout app, which objectives to assist those with low or no imaginative and prescient name things around them.

A brand contemporary update has added the ability for a computer direct to bid aloud what meals it thinks a person is retaining in accordance with its visual appearance.

One UK blindness charity welcomed the transfer, announcing it can most likely perchance assist boost blind other folks’s independence.

Google says the feature will “be able to distinguish between a can of corn and a can of inexperienced beans”.

Peek-catching, now no longer uncomplicated

Many apps, equivalent to calorie trackers, maintain prolonged used product barcodes to call what you’ll also very well be eating. Google says Lookout is furthermore utilizing image recognition to call the product from its packaging.

The app, for Android telephones, has some two million “standard merchandise” in a database it stores on the phone – and this catalogue adjustments looking on the effect the person is on this planet, a post on Google’s AI weblog acknowledged.

In a kitchen cupboard take a look at by a BBC reporter, the app had no wretchedness in recognising a favored label of American sizzling sauce, or one other the same product from Thailand. It may perchance perhaps truly furthermore appropriately learn spices, jars and tins from British supermarkets – besides to imported Australian favourite Vegemite.

But it absolutely fared less well on tranquil impact or containers with irregular shapes, equivalent to onions, potatoes, tubes of tomato paste and luggage of flour.

If it had disaster, the app’s direct asked the person to curl the bundle to 1 other attitude – but tranquil failed on several items.

The UK’s Royal National Institute of Blind Of us (RNIB) gave a cautious welcome to the contemporary feature.

“Food labels will be strong for somebody with a visual impairment, as they are in total designed to be peer-catching in preference to uncomplicated to learn,” acknowledged Robin Spinks from the charity.

“Ideally, we would fancy to peek accessibility constructed into the impact course of for labels in recount that they are less complicated to navigate for partly sighted other folks.”

But alongside with other the same apps – equivalent to Be My Eyes and NaviLens, that are furthermore on hand on iPhones – it “may perchance presumably perhaps assist boost independence for folks with gape loss by identifying merchandise rapidly and with out problems”.

Media playback is unsupported for your machine

Media captionBe My Eyes: How smartphones became ‘eyes’ for blind other folks

Lookout uses the same skills to Google Lens, the app that may perchance presumably name what a smartphone camera is taking a explore at and gift the person extra recordsdata. It already had a mode that may perchance presumably perhaps learn any text it became as soon as pointed at, and an “explore mode” that identifies objects and text.

Launching the app closing year, Google suggested inserting a smartphone in a front shirt pocket or on a lanyard around the neck so the camera may perchance perhaps name things straight away in front of it.

One other contemporary characteristic added within the update is a scan doc feature, which takes a photo of letters and other documents and sends it to a conceal reader to be learn aloud.

Google furthermore says it has made improvements to the app in accordance with feedback from visually impaired users.

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[coopdigitalnewsletter]

10 June 2020: Could 5G help make shopping centres safe instead of smart? Black lives matter: #teagate

Hello, this is the Co-op Digital newsletter - it looks at what's happening in the internet/digital world and how it's relevant to the Co-op, to retail businesses, and most importantly to people, communities and society. Thank you for reading - send ideas and feedback to @rod on Twitter. Please tell a friend about it!

[Image: Apple Maps, which pushed out a quick edit to their satellite imagery]

Could 5G help make shopping centres safe instead of smart?

“UK's first smart mall blazes a trail for physical retail: Can 5G technology turn shopping centres back into attractive destinations?” The promise in this story is that 5G bandwidth plus augmented reality will transform a Surrey shopping centre’s shops into an exciting physical/virtual hybrid:

“tapping a phone over a product's barcode will trigger an overlay of digital content that can reveal the entire provenance of the supply chain for checking ethical credentials or ingredient detail. [...] It's like squashing the range you would otherwise get in Selfridges into something the size of Clinton cards but still with the ability to pick something up [in store] and have that physical interaction with the assistant"

(Well, stuffing Selfridges into a Clinton Cards is one way of selling the magic.) This idea isn’t new but it is interesting. Argos, Screwfix and shoe shops already separate display from inventory. And online shopping separates both display from inventory and the transaction from possession of the goods. Splitting things apart (or “unbundling”) can be a good way to create some new value. In physical retail, the unbundling value is generally about cost efficiencies. This might be the challenge for smart shopping centres: are they offering the right bundle? And if the value a smarter shopping centre creates is cost efficiency, how does it compete with the modern cost efficiency experts, online shopping? And will it be happy if shoppers “showroom”: inspect the item in the shop, and then use that convenient 5G to see if they can buy it cheaper online? There is a solutioneering feel about that news story - maybe they wondered if a problem could be found to go with the collection of technologies they had in front of them. 

Instead, what if they started with needs? Instead of “smart” or “cost-efficient Selfridges”, what if they’d started with “safe”? Perhaps a shopping centre could make coronashopping very safe by managing queues and distancing really well. Or by providing booked entry times paired with sensible deals. Or by monitoring what percentage of people are currently wearing masks. Or by providing click and collect from mezzanine level 4 to the car park. Safe shopping is going to be a thing as it becomes clearer that the coronavirus is something we’ll live with for a long time. Can 5G help with any of this?

Related: coronavirus is accelerating wealth inequalities in offline retail, with high margin sectors able to offer bespoke, socially-distanced service and lower margin sectors offering queues.

Black lives matter: #teagate

Yorkshire Tea and PG Tips said please don’t buy our tea to some people on Twitter. Hats off to them. Last week we wondered whether brands will all take political positions eventually, because the world’s increased inequality and rate of change will force them to.

However tea isn’t quite as simple as a binary good vs bad though: tea has a complicated colonial history. Race, racism and history are woven into the everyday - read this powerful piece, by Co-op’s Annette Joseph. We have to work at making everything better. 

Amazon as a COVID green zone?

Amazon could spend $300m on developing COVID-19 testing by the summer. And the company says it will spend $4bn total on virus-related efforts in the next financial quarter. Some of that 4bn is going on PPE, testing, social distancing measures etc, like every other retail company is doing. But the wider aim might be a fully “vaccinated supply chain”, a covid-secured organisation and logistics operation in which both employees and customers feel safer. 

You buy from them because it’s reliable, or maybe you even go work for them. (That’s the theory anyway, though Amazon’s history of warehouse worker complaints suggest it’s not going to be quite as easy as that.) What stops others doing this? If only Amazon has the cashflow to do it, then it might create competitive advantage, and even deeper moat for the Everything Store.

Clapping robots will deliver more Co-op grocery orders

Co-op is expanding same-day robot-delivered groceries to more stores and communities near Milton Keynes:

“The number of customers using robot deliveries has more than doubled since the start of lockdown, with the value of transactions increasing four-fold as shopping habits change. In response to the rising demand, the service has been made available in eight Co-op Group stores, with six new stores added since March.

“Starship has also waived its delivery charge for NHS workers during the lockdown period - and programmed the robots to pause to “clap and cheer” at 8pm on Thursday evenings in recognition of carers and key workers.” [!]

Content writerbots and content moderation farms

Microsoft sacks journalists to replace them with robots gathering stories for MSN.com: “I spend all my time reading about how automation and AI is going to take all our jobs, and here I am – AI has taken my job.” You didn’t need to be a neural network to predict what would happen next: Microsoft's robot editor confuses mixed-race Little Mix singers. And it sounds as if the remaining journohumans at MSN are struggling to control the AI’s driving need to publish stories about its own bias. “Now is not the time to be making mistakes”, says a Microsoft staff member. (Oh! Or maybe this is an elaborate scheme to keep journalists in work, battling their AI colleagues?)

So far content moderation has been difficult to automate, so social media cos typically outsource content moderation to contractors. A new report says that reliance of contractors has led to poor working conditions and a lack of attention to real-world harms caused by inflammatory or deceptive content. Content moderation should be brought in house, it recommends. (More on outsourced content moderation, though that can be a difficult read.)

Various things

Big salute to Doteveryone, which is stopping work after five years of fighting for better tech, for everyone.

Behavioural insurance startup Lemonade will go public.

Ploipailin Flynn wrote a powerful month note for Projects by IF about anti-racism.

Zoom says free users won’t get end-to-end encryption so FBI and police can access calls - that seems a really bad way to think about who deserves privacy, but sadly you’ll probably see more of it in future.

Co-op Digital news

We’re using ‘behaviour modes’ to keep users at the centre of decisions.

Co-op Group’s annual general meeting.

The Federation House team is running weekly drop-in chats for the community every Wednesday at 10am: Join us here. See our online events.

Free of charge 

Andy’s Man Club – Gentleman's Peer to Peer Mental Health Meet Up – Mondays 7pm 

Self-Care – Online Workshops – Various dates/times in June 

Virtual Cloud Native + Kubernetes – Meet Up – 10 June – 6pm  

Northern Azure User Group – Meet Up – 10 June – 7pm  

Let’s Talk Service Design – Lightning Talks – 25 June – 12pm 

 Paid for 

Mental Health – 2 Day Training Course – 15/16 June – All Day 

Cariad Yoga – Online Yoga – Various Dates & Times in June 

Invisible Cities - Online Tours of Manchester or Edinburgh – Various Dates & Times 

Thank you for reading

Thank you, beloved readers and contributors. Please continue to send ideas, questions, corrections, improvements, etc to the newsletter’s typist @rod on Twitter. If you have enjoyed reading, please tell a friend!

If you want to find out more about Co-op Digital, follow us @CoopDigital on Twitter and read the Co-op Digital Blog. Previous newsletters.

[haab-blog]

Advancing Computer Vision by Leveraging Humans

Abstract: Historically, humans have played a limited role in advancing the challenging problem of computer vision: either by designing algorithms in their capacity as researchers or by acting as ground-truth generating minions. This seems rather counter-productive since we often aim to replicate human performance (e.g. in semantic image understanding) and we desire humans to communicate with vision systems (e.g. in image search, or for training the systems). In this talk, I will describe my recent efforts in expanding the roles humans play in advancing computer vision.

In the first part of my talk, I will describe our recently-introduced “human-debugging” paradigm. It allows us to identify weak-links in machine vision approaches that require further research. It involves replacing subcomponents of machine vision pipelines with human subjects, and examining the resultant effect on overall recognition performance. I will present several of our efforts within this framework that address image classification, object recognition and person detection. I will discuss the lessons learnt and present subsequent improvements to computer vision algorithms inspired by these findings.

In the second part of my talk, I will present our work on allowing humans and machines to better communicate with each other by exploiting visual attributes. Visual attributes are mid-level concepts such as “furry” and “metallic” that bridge the gap between low-level image features (e.g. texture) and high-level concepts (e.g. rabbit or car). They are shareable across different but related concepts. Most importantly, visual attributes are both machine detectable and human understandable, making them ideal as a mode of communication between the two. I will present our work on discovering a vocabulary of these attributes in the first place and on enhancing the communication power of these attributes by using them relatively. We utilize attributes for a variety of applications including improved image search and effective active learning of image classifiers.

Speaker: Devi Parikh is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech (VT), where she leads the Computer Vision Lab. She is also a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC).

Prior to this, she was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), an academic computer science institute affiliated with University of Chicago. She has held visiting positions at Cornell University, University of Texas at Austin, Microsoft Research, MIT and Carnegie Mellon University. She received her M.S. and Ph.D. degrees from the Electrical and Computer Engineering department at Carnegie Mellon University in 2007 and 2009 respectively. She received her B.S. in Electrical and Computer Engineering from Rowan University in 2005.

Her research interests include computer vision, pattern recognition and AI in general and visual recognition problems in particular. Her recent work involves leveraging human-machine collaborations for building smarter machines. She has also worked on other topics such as ensemble of classifiers, data fusion, inference in probabilistic models, 3D reassembly, barcode segmentation, computational photography, interactive computer vision, contextual reasoning and hierarchical representations of images.

She was a recipient of the Carnegie Mellon Dean’s Fellowship, National Science Foundation Graduate Research Fellowship, Outstanding Reviewer Award at CVPR 2012, Google Faculty Research Award in 2012 and the 2011 Marr Best Paper Prize awarded at the International Conference on Computer Vision (ICCV). Likes: 1 Viewed:

The post Advancing Computer Vision by Leveraging Humans appeared first on Good Info.

[rakinda01]

LV30 2d barcode scanner embedded in PDA for Medical industry

with the advancement of medical science and technology reforms, mobile medical care has become an essential tool for modern medical care. Doctors and nurses can quickly see the latest status of patients through medical tablet terminals, reduce the work intensity of medical staff, and thus improve the level of medical care. It is reported that a smart hospital in Shenzhen is able to learn about patients' medication, blood transfusion, sample collection, and treatment through medical tablets.Why is the medical tablet so magical to know the patient? According to the hospital staff, in fact, the hospital established a bar code scanner system for wristbands. Each hospitalized patient wears a bar code wristband. The patient's barcode wristbands all have a unique coded information wristband. This is also a medication for patients. corresponding. By embedding a 2d scanner module on a medical tablet, medical personnel can quickly and accurately know the patient's medication status by using a medical tablet to scan barcode wristbands and medicine bar code information.

LV30 bar code reading engine, the application of the world's leading chip smart recognition technology to create a new era of image-based 2d bar code reading scanner engine.LV30 has many advantage which has four modes : trigger reading mode , continuous , auto sensing , command control mode ,  and LV 30 is  popular use in tablet.

RAKINDA is a company committed to the development up to barcode scanner technology at the core of the automatic identification system integration organizations, enjoyed several years of industry experience and excellent reputation, in Shenzhen and Hong Kong branches, and has a very skillful, experienced, innovative R & D and after-sales technical support service team. Rakinda Group, the manufacturer of barcode scanner module, was established in 2000. We have offices in Guangzhou, Shenzhen, Hongkong, Xiamen, Suzhou and Beijing. And we have been supplying the barcode scanner module for Walmart, Carrefour and Foxconn etc. Any questions do not hesitate contact me as below.

[trrrrrrrrravel-blog]

Mobile phones from various years A mobile or cell(ular) (tele)phone is a long-range, portable electronic device for personal telecommunications over long distances. Most current mobile phones connect to a cellular network of base stations (cell sites), which is in turn interconnected to the public switched telephone network (PSTN) (the exception are satellite phones). Cellular networks were first introduced in the early to mid 1980s (the 1G generation). Prior mobile phones operating without a cellular network (the so-called 0G generation), such as Mobile Telephone Service, date back to 1945. Until the mid to late 1980s, most mobile phones were sufficiently large that they were permanently installed in vehicles as car phones. With the advance of miniaturization, currently the vast majority of mobile phones are handheld. In addition to the standard voice function of a telephone, a mobile phone can support many additional services such as SMS for text messaging, email, packet switching for access to the Internet, and MMS for sending and receiving photos and video. The world's largest mobile phone manufacturers include Audiovox, BenQ-Siemens, High Tech Computer Corporation, Fujitsu, Kyocera, LG, Motorola, NEC, Nokia, Panasonic (Matsushita Electric), Pantech Curitel, Philips, Sagem, Samsung, Sanyo, Sharp, SK Teletech, Sony Ericsson, T&A Alcatel and Toshiba. The world's largest mobile phone operators include Orange SA, China Mobile and Vodafone. There are also specialist communication systems related to, but distinct from mobile phones, such as Professional Mobile Radio. Mobile phones are also distinct from cordless telephones, which generally operate only within a limited range of a specific base station. Technically, the term mobile phone includes such devices as satellite phones and pre-cellular mobile phones such as those operating via MTS which do not have a cellular network, whereas the related term cell(ular) phone does not. In practice, the two terms are used nearly interchangeably, with the preferred term varying by location. World mobile phone usage In most of Europe, wealthier parts of Asia, Africa, the Caribbean, Latin America, Australia, Canada, and the United States, mobile phones are now widely used, with the majority of the adult, teenage, and even child population owning one. Taiwan had the highest mobile phone usage in 2005 at 111 subscribers per 100 people. Hong Kong has the highest mobile phone penetration rate in the world, at 127.4% in June 2006. The total number of mobile phone subscribers in the world was estimated at 2.14 billion in 2005. At present India and China have the largest growth rates of cellular subscribers in the world. The availability of Prepaid or pay as you go services, where the subscriber does not have to commit to a long term contract, has helped fuel this growth on a monumental scale. The mobile phone has become ubiquitous because of the interoperability of mobile phones across different networks and countries. This is due to the equipment manufacturers working to meet one of a few standards, particularly the GSM standard which was designed for Europe-wide interoperability. All European nations and most Asian and African nations adopted it as their sole standard. In other countries, such as the United States, Australia, Japan, and South Korea, legislation does not require any particular standard, and GSM coexists with other standards, such as CDMA and iDEN. Mobile phone culture or customs In fewer than twenty years, mobile phones have gone from being rare and expensive pieces of equipment used by businesses to a pervasive low-cost personal item. In many countries, mobile phones now outnumber land-line telephones, with most adults and many children now owning mobile phones [citation needed]. In the United States, 50% of children own mobile phones. It is not uncommon for young adults to simply own a mobile phone instead of a land-line for their residence [citation needed]. In some developing countries, where there is little existing fixed-line infrastructure, the mobile phone has become widespread. According to the CIA World Factbook the UK now has more mobile phones than people . With high levels of mobile telephone penetration, a mobile culture has evolved, where the phone becomes a key social tool, and people rely on their mobile phone address book to keep in touch with their friends. Many people keep in touch using SMS, and a whole culture of "texting" has developed from this. The commercial market in SMS's is growing. Many phones even offer Instant Messenger services to increase the simplicity and ease of texting on phones. Cellular phones in Japan, offering Internet capabilities such as NTT DoCoMo's i-mode, offer text messaging via standard e-mail. The mobile phone itself has also become a totemic and fashion object, with users decorating, customizing, and accessorizing their mobile phones to reflect their personality. This has emerged as its own industry. The sale of commercial ringtones exceeded $2.5 billion in 2004. The use of a mobile phone is prohibited in some rail carriages Mobile phone etiquette has become an important issue with mobiles ringing at funerals, weddings, movies, and plays. Users often speak at increased volume which has led to places like bookshops, libraries, movie theatres, doctor's offices, and houses of worship posting signs prohibiting the use of mobile phones, and in some places installing signal jamming equipment to prevent usage (although in many countries, e.g. the United States, such equipment is illegal). Transportation providers, particularly those doing long-distance services, often offer a "quiet car" where phone use is prohibited, much like the designated non-smoking cars in the past. Mobile phone use on aircraft is also prohibited, because of concerns of possible interference with aircraft radio communications. Most schools in the U.S prohibit cell phones due to the high amount of class disruptions due to their use, and due to the possibility of photographing someone (without consent). In Japan, cellular phone companies provide immediate notification of earthquakes and other natural disasters to their customers free of charge. In the event of an emergency, disaster response crews can locate trapped or injured people using the signals from their mobile phones; an interactive menu accessible through the phone's Internet browser notifies the company if the user is safe or in distress. Mobile phone features Main article: Mobile phone features Invented in 1997, the camera phone is now 85% of the market. Mobile phones also often have features beyond sending text messages and making voice calls—including Internet browsing, music (MP3) playback, personal organizers, e-mail, built-in cameras and camcorders, ringtones, games, radio, Push-to-Talk (PTT), infrared and Bluetooth connectivity, call registers, ability to watch streaming video or download video for later viewing, and serving as a wireless modem for a PC. In most countries, the person receiving a cellular phone call pays nothing. However, in China (including Hong Kong), Canada, and the United States, one can be charged per minute. Future prospects There is a great deal of active research and development into mobile phone technology that is currently underway. Some of the improvements that are being worked on are: Now that operators are upgrading their networks to advanced wireless and other third-generation (3G) services, many new entertainment and communications services are becoming available, including new broadcast-type operations on spectrum formerly occupied by Television Channels 52-69. With downlink speeds comparable to that of wireline DSL, mobile service can now offer capabilities such as streaming video sharing and music downloads. Services such as MobiTV, Digital Mobile TV or Juice Caster are just some examples of applications that leverage these new networks. One difficulty in adapting mobile phones to new uses is form factor. For example, ebook readers may well become a distinct device, because of conflicting form-factor requirements — ebook readers require large screens, while phones need to be smaller. However, this may be solved using folding e-paper or built-in projectors. One function that would be useful in phones is a translation function. Currently it is only available in stand-alone devices, such as Ectaco translators. An important area of evolution relates to the Man Machine Interface. New solutions are being developed to create new MMI more easily and let manufacturers and operators experiment new concepts. Examples of companies that are currently developing this technology are Digital Airways with the Kaleido product, e-sim, mobile arsenal, and Qualcomm with uiOne for the BREW environment. Mobile phones will include various speech technologies as they are being developed. Many phones already have rudimentary speech recognition in a form of voice dialing. However, to support more natural speech recognition and translation, a drastic improvement in the state of technology in these devices is required. New technologies are being explored that will utilize the Extended Internet and enable mobile phones to treat a barcode as a URL tag. Phones equipped with barcode reader-enabled cameras will be able to snap photos of barcodes and direct the user to corresponding sites on the Internet. This technology can be extended to RFID tags, or even snapped pictures of company logos. Searches can also be personalized to local areas using a GPS system built in to cell phones. Examples of companies that are currently developing this technology are Nextcode, OP3, Neomedia Technologies, and Scanbuy, the latter of which is currently being sued by Neomedia for patent infringement. Another approach (used by jumptag.com) is to map URLs to short text tags tailored for easy user entry on phone keypads. Developments in miniaturized hard disks and flash d

[harshalblogs-blog]

Smart Baggage Handling System Market to Rise at 19.3% CAGR

Global Smart Baggage Handling System Market: Snapshot

In a competitive global smart baggage handling system market, keen players are hard-focused on collaborations to expand their outreach and to accelerate their pace of gains. In matters of competition, the global smart baggage handling system market is expected to witness the entry of small-sized players that will further intensify competition in this market.

Some of the key growth drivers of the global smart baggage handling system market are a modernization of existing airports, growth in the number of airports and air travelers, and adoption of systems with improved accuracy for baggage handling and baggage tracking.

In emerging economies, construction of new airports that are equipped with state-of-the-art technology is benefiting the smart baggage handling system market. The installation of these systems enable easy tracking and handling a large volume of baggage which is critical to the growing air traffic in these regions.

Read Report Sample @

https://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=30998

As per estimates of a report by Transparency Market Research, the global smart baggage handling system market will clock an impressive 19.3% CAGR from 2017 to 2025. If the figure holds true, the market’s valuation of US$1,508.6 mn in 2106 will become US$7,210.8 mn by the end of 2025.

Radio Frequency Identification Scanning Technology Preferred due Virtues of Reliability

The report studies the global smart baggage handling system market on the basis of mode of transportation, technology, solution, and region. In terms of airport, the market is segmented into airport and railway station. The segments of the global smart baggage handling system market based on technology are radio frequency identification system (RFID) and barcode system. Of the two, in 2016, radio frequency identification led the market vis-à-vis revenue. This is because RFID allows the system to scan the baggage tags with negligible probability of issues that help generate a good chunk of revenue.

On the basis of mode of transportation, the global smart baggage handling system market is divided into airport and railway station. The segment of airport is further sub-segmented into international and domestic. The international airport segment is expected to represent a sizeable share of the overall market over the forecast period.

The segments of the market depending upon solution are sorting, conveying, tracking and tracing, diverting, and others.

Read Report Brochure @

https://www.transparencymarketresearch.com/sample/sample.php?flag=B&rep_id=30998

Powered by the U.S., North America to Display Robust CAGR through 2025

Geography-wise, the report studies the growth prospects of the global smart baggage handling system market across North America, Europe, Asia Pacific, the Middle East and Africa, and South America. North America is the key region for smart baggage handling systems due to a significant growth in the construction of new airports in the last couple of years. The North America smart baggage handling system market is anticipated to display a phenomenal 20.5% CAGR over the forecast period between 2017 and 2025. The U.S. currently accounts for the leading revenue contribution to the region and going forward the U.S. is estimated to rise at a significant CAGR over the forecast period. The U.S. federal government recently invested approximately US$3.7 bn to strengthen airport infrastructure. This includes installation of high capacity automated baggage handling systems to serve the need to handle large volume of baggage of varying sizes. Air carriers as well airports authority are working in coherence to deploy advanced baggage handling systems across North America. For instance, in May 2017, Delta Airlines invested US$442.3 bn to include facial recognition for passengers using self-service baggage drop system at Atlanta International Airports.

In 2016, Asia Pacific stood as a key region for smart baggage handling system due to growth in the number of airports and air travelers.

Prominent participants in the global smart baggage handling system market include Daifuku Web Siemens Group, Pteris Global Limited, Fives Group, G&S Airport Conveyor, Vanderlande Industries, Alstef Automation S.A., SITA, Beumer Group, and Scarabee Systems & Technology B.V.

[marketresearchinsight-blog]

Image Recognition Market - Challenges, Opportunities, Top Companies And Future Growth Scope

San Francisco, 11 July 2019 — The global image recognition market size is expected to reach USD 77.69 billion by 2025, according to a new report by Grand View Research, Inc., reporting a 19.2% CAGR during the forecast period.

Image recognition technology plays a crucial role in information technology (IT) and online visual revolution, owing to growth in digitization. Rising popularity of media cloud services and mobile devices equipped with cameras has resulted in the growing trend of experience sharing on the web. This, in turn, has resulted in increased digital data, particularly unstructured multimedia data, which majorly comprises images and videos.

Images and videos reflect a good part of human conversations, interactions, and knowledge, which have led to substantial opportunities to create new products, applications, and use cases. This has driven the growth of image recognition technology. However, large storage requirement for multimedia data and analyzing low-resolution images may pose a challenge to the growth of market.

Image recognition technology detects and identifies objects and features in a digital image and works with the help of various types of algorithms, such as optical character recognition, pattern matching and gradient matching, and face recognition, which are being developed on a daily basis. It has numerous applications such as publishing, traffic management, advertising, e-commerce, and security. Image recognition technology has witnessed several opportunities, such as big data analytics and effective branding of products and services, owing to the extending reach of image database. Some of these databases, such as ImageNet and Pascal VOC, are freely available. The database contains millions of keyword-tagged images that describe objects present in the image. It forms the basis for image recognition and enables computers to accurately and quickly identify objects in the picture.

Rising popularity of image recognition technology is encouraging manufacturers to invest in research and development for creating reliable, cost-effective, and improved products and solutions. Existing players are continuously making substantial investments to develop new products for providing enhanced user experience.

To request a sample copy or view summary of this report, click the link below: https://www.grandviewresearch.com/industry-analysis/image-recognition-market

Further key findings from the report suggest:

Easy Internet accessibility, along with growing popularity of social media, has led to growth in demand for image recognition technology

Rising use of smartphones and large investments made by smartphone vendors such as Huawei and Apple to add AI capabilities to their smartphones are fueling market growth

Increasing demand of the virtual market and rising number of unstructured multimedia data are creating immense market potential for image recognition solutions

Growing integration of image recognition and mobile computing platforms in various applications such as digital shopping and document verification are propelling market growth

Key industry participants include Catchoom (Spain); Google, Inc. (U.S.); LTU Technologies (France); NEC Corporation (Japan); and Qualcomm Incorporated (U.S.).

Grand View Research has segmented the global image recognition market based on technique, application, component, deployment mode, vertical, and region:

Image Recognition Technique Outlook (Revenue, USD Million, 2014–2025)

QR/Barcode Recognition

Object Recognition

Facial Recognition

Pattern Recognition

Optical Character Recognition

Image Recognition Application Outlook (Revenue, USD Million, 2014–2025)

Augmented Reality

Scanning & Imaging

Security & Surveillance

Marketing & Advertising

Image Search

Image Recognition Component Outlook (Revenue, USD Million, 2014–2025)

Hardware

Software

Service

Image Recognition Deployment Mode Outlook (Revenue, USD Million, 2014–2025)

On-Premise

Cloud

Image Recognition Vertical Outlook (Revenue, USD Million, 2014–2025)

Retail & E-commerce

Media & Entertainment

BFSI

Automobile & Transportation

Telecom & IT

Government

Healthcare

Others

Image Recognition Regional Outlook (Revenue, USD Million, 2014–2025)

North America

US.

Canada

Mexico

Europe

Germany

UK.

Asia Pacific

China

Japan

India

South America

Brazil

Middle East & Africa

Browse Press Release of this Report: https://www.grandviewresearch.com/press-release/global-image-recognition-market

About Grand View Research

Grand View Research, Inc. is a U.S. based market research and consulting company, registered in the State of California and headquartered in San Francisco. The company provides syndicated research reports, customized research reports, and consulting services. To help clients make informed business decisions, we offer market intelligence studies ensuring relevant and fact-based research across a range of industries, from technology to chemicals, materials and healthcare.

For More Information: www.grandviewresearch.com

[superaakash24]

Learn Complete Data Science Tutorial just in 8 minute

1. Data Science Tutorial – Objective

This Data Science tutorial aims to guide you to the world of data science and get you started with the basics like what is Data Science, History of Data Science, and Data Science Methodologies. Here, we will cover the Data Science Applications, a difference between Business Intelligence and Data Science. Along with this, we will discuss Life-Cycle of Data Science and Python Libraries.

So, let’s begin Data Science Tutorial.

Data Science Tutorial – Introduction to Data Science with Python

2. What is Data Science?

Before we start the Data Science Tutorial, we should find out what data science really is.

Data science is a way to try and discover hidden patterns in raw data. To achieve this goal, it makes use of several algorithms, machine learning(ML) principles, and scientific methods. The insights it retrieves from data lie in forms structured and unstructured. So in a way, this is like data mining. Data science encompasses all- data analysis, statistics, and machine learning. With more practices being labelled into data science, the term itself becomes diluted beyond usefulness. This leads to variation in curricula for introductory data science courses worldwide.

Do you know the Best Data Scientist Certifications to Choose from

3. Data Science Tutorial – History

Through the recent hype that data science has picked up, we observe that it has been around for over thirty years. What one we could use as a synonym for practices like business analytics, business intelligence, or predictive modeling, now refers to a broad sense of dealing with data to find a relationship within it. To quote a timeline, it would go something like this:

a. In 90’s

1960- Peter Naur uses the term as a substitute for computer science.

1974- Peter Naur publishes Concise Survey of Computer Methods, uses a term in a survey of contemporary data processing methods.

1996- Biennial conference in Kobe; members of the IFCS (International Federation of Classification Societies include the term in the conference title.

1997- November- Professor C.F. Jeff Wu delivers inaugural lecture on the topic “Statistics=Data Science?”.

b. In 20’s

2001- William S. Cleveland introduces data science as an independent discipline in article Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics.

2002- April- The ICSU (International Council for Science): Committee on Data for Science and Technology (CODATA) starts Data Science Journal- this publication is to focus on issues pertaining to data systems- description, publication, application, and also legal issues.

2003- January- Columbia University publishes journal The Journal of Data Science- a platform that allows data workers to exchange ideas.

2005- National Science Board publishes Long-lived Digital Data Collections: Enabling Research and Education in the 21st Century- this provides a new definition to the term “data scientists”.

2007- Jim Gray, Turing awardee, envisions data-driven science as the fourth paradigm of science.

2012- Harvard Business Review article attributes coinage of the term to DJ Patil and Jeff Hammerbacher in 2008.

2013- IEEE launches a task force on Data Science and Advanced Analytics; first European Conference on Data Analysis (ECDA)organized in Luxembourg, European Association for Data Science (EuADS) comes into existence.

2014- IEEE launches first international conference International Conference on Data Science and Advanced Analytics; General Assembly launches student-paid Bootcamp, The Data Incubator launches data science fellowship for free.

2015- Springer launches International Journal on Data Science and Analytics.

4. Data Science Tutorial – Methodologies

In this Data Science Tutorial, we will cover the following Methodologies in data Science:

Data Science Tutorial – Methodologies of Data Science

a. Machine Learning for Pattern Discovery

With this, clustering comes into play. This is an algorithm to use to discover patterns; an unsupervised model. When you don’t have parameters on which to make predictions, clustering will let you find hidden patterns within a dataset.

One such use-case is to use clustering in a telephone company to determine tower locations for optimum signal strength.

b. Machine Learning for Making Predictions

When we have the data we need to train our machine, we can use supervised learning to deal with transactional data. Making use of machine learning algorithms, we can build a model and determine what trends the future will observe.

c. Predictive Causal Analytics

Causal analytics lets us make predictions based on a cause. This will tell us how probable an event is to hold occurrence in future. One use-case will be to perform such analytics on payment histories of customers in a bank. This tells us how likely customers are to reimburse loans.

d. Prescriptive Analytics

Predictive analysis will prescribe your actions and the outcomes associated with those. This intelligence lets it take decisions and modify those using dynamic parameters. For a use-case, let us suggest the self-driving car by Google. With the algorithms in place, it can decide when to speed up or slow down, when to turn, and which road to take.

Have a look at – 30 Most Popular Data Science Interview Questions

5. Data Science Applications

Let’s see some applications in this Data Science Tutorial:

Data Science Tutorial – Data Science Applications

a. Image Recognition

Using the face recognition algorithm of data science, we can get a lot done. Did Facebook ever suggest people tag in your pictures? Have you tried the search-by-image feature from Google? Do you remember scanning a barcode to log in to WhatsApp Web using your smartphone?

b. Speech Recognition

Siri, Alexa, Cortana, Google Voice all make use of speech recognition to understand your commands. Attributing to issues like different accents and ambient noise, this isn’t always completely accurate, though intelligible most of the time. This facilitates luxury like speaking the content of a text to send, using your virtual assistant to set an alarm, or even use it to play music, inquire about the weather, or make a call.

c. Internet Search

Search engines like Google, Duckduckgo, Yahoo, and Bing make good use of data science to make fast, real-time searching possible.

d. Digital Advertisements

Data science algorithms let us understand customer behaviour. Using this information, we can put up relevant advertisements curated for each user. This also applies to advertisements as banners on websites and digital billboards at airports.

e. Recommender Systems

Names like Amazon and Youtube will throw in suggestions about similar products aside or below as you browse through a product or a video. This enriches the UX(user experience) and helps retain customers and users. This will also take into account the user’s search history and wishlist.

Let’s explore the Future of Data Science – Data Science Career Prospects

f. Price Comparison Websites

Websites like Junglee and PriceDekho let us compare prices for the same products across different platforms. This facility lets you make sure you grab the best deal. These websites work in the domains of technology, apparel, and policy among many others, and use APIs and RSS feeds to fetch data.

g. Gaming

As a player levels up, a machine learning algorithm can improve or upgrade itself. It is also possible for the opponent to analyze the player’s moves and add an element of difficulty to the game. Companies like Sony and Nintendo make use of this.

h. Delivery Logistics

Freight giants like UPS, FedEx, and DHL use practices of data science to discover optimal routes, delivery times, and transport modes among many others. A plus with logistics is the data obtained from the GPS devices installed.

i. Fraud and Risk Detection

Practices like customer profiling and past expenditures let us analyze whether there will be a failure. This lets banks avoid debts and losses.

6. Business Intelligence vs Data Science

Here, in this part of Data Science Tutorial, we discuss Data Science Vs BI. Business intelligence and data science aren’t exactly the same thing.

BI works on structured data; data science works on both- structured and unstructured data.

Where BI focuses on the past and the present, data science considers the present and the future.

The approach to BI is statistics and visualization; that to data science is statistics, machine learning, graph analysis, and NLP.

Some tools for BI are Pentaho, Microsoft BI, and R; those for data science are RapidMiner, BigML, and R.

Let’s Explore the Difference Between Data Science vs Data Analytics

7. Data Science Tutorial – Life-Cycle

The journey with data science goes through six phases

a. Discovery

Before anything else, you should understand what the project requires. Also consider the specifications, the budget needed, and priorities. This is the phase where you frame the business problem and form initial hypotheses.

b. Data Preparation

In the preparation phase, you will need to perform analytics in an analytical sandbox. This is for an entire project. You will also extract, transform, load, and transform data into the sandbox.

c. Model Planning

In the third phase, you choose the methods you want to work with to find out how the variables relate to each other. This includes carrying out Exploratory Data Analytics (EDA) making use of statistical formulae and visualization tools.

d. Model Building

This phase includes developing datasets for training and testing. It also means you will have to analyze techniques like classification and clustering and determine whether the current infrastructure will do.

e. Communicate results

This is the second last phase in the cycle. You must determine whether your goals have been met. Document your findings, communicate to stakeholders, label the project a success or failure. Do you know the Skills Needed to Become a Data Scientist

f. Operationalize

In the last phase, you must craft final reports, technical documents, and briefings

This Data Science Tutorial is dedicated to Python. So, let’s start Data Science for Python.

8. Data Science Tutorial – Why Python?

So, now you know what data science is all about. But why is Python the best choice for it? Here are a few reasons-

Open-source and free.

Easy to learn; intuitive.

Fewer lines of code.

Portability.

Better productivity.

Demand and popularity.

Excellent online presence/ community.

Support for many packages usable with analytics projects; can also use packages that can use code from other languages.

It is faster than similar tools like R and MATLAB.

Amazing memory management abilities.

Follow this link to know more about Why we learn Python Programming Language

9. Python 2.x or 3.x- Which should you go for?

Among a lot of other factors, the support for Python 2 ends officially on January 1st, 2020, so the future belongs to Python 3. Also, 95% of the libraries for data science are done being migrated from Python 2 to Python 3. Apart from that, Python 3 is cleaner and faster.

Well, then what about Python 2? It has its own perks- it is rich with a large online community and plenty of third-party libraries, and some features are backwards-compatible and work with both versions.

With the perks of each version listed, make your choices.

10. Data Science Tutorial – Python Libraries

For carrying out data analysis and other scientific computation, you will need any of the following libraries:

Data Science Tutorial – Data Science Libraries

a. Pandas

Pandas help us with munging and preparing data; it is great for operating on and maintaining structured data.

b. SciPy

SciPy (Scientific Python) stands on top of NumPy. With this library, we can carry out functionality like Linear Algebra, Fourier Transform, Optimization, and many others.

c. NumPy

NumPy (Numerical Python) is another library that lets us deal with features like linear algebra, Fourier transforms and advanced random number capabilities. One very import feature of NumPy is the n-dimensional array.

d. Matplotlib

Matplotlib will let you plot different kinds of graphs. These include pie charts, bar graphs, histograms, and even heat plots.

e. Scikit-learn

Scikit-learn is great for machine learning. It will let you statistically model and implement machine learning. The tools for these include clustering, regression, classification, and dimensionality reduction.

f. Seaborn

Seaborn is good with statistical data visualization. Making use of it, we can create useful and attractive graphics.

g. Scrapy

Scrapy will let you crawl the web. It begins on a home page and gets deeper within a website for information.

Follow this link to know more about Python Libraries in detail

11. Learning in Data Science Tutorial

Before you begin with data science Tutorials, we suggest you should brush up on the following:

Variables in Python

Operators in Python

Dictionaries in Python

Strings in Python

Python Lists

Python Tuples

So, this was all about Data Science Tutorial. Hope you like our explanation.

12. Conclusion

Hence, we complete this Data Science Tutorial, in which we learned: what is Data Science, History of Data Science, and Data Science Methodologies. In addition, we covered the Data Science Applications, BI Vs Data Science. At last, we discussed Life-Cycle of Data Science and Python Libraries. This will get you started with Python.

Got something else to add in this Data Science Tutorial? Drop it in the comments below.

[iaccessibility]

Product Comparison: OrCam VS Seeing A.I.

We at iAccessibility, from time to time,  like to compare two products  to see which one is more practical, and which one works best. Today, we decided to take a look at Seeing AI and OrCam, as both of these products have similar features, but different form factors. Lets start with going over each product and what it can accomplish.

OrCam MyEye

The OrCam MyEye is a fantastic product that is basically a camera  mounted on standard glasses. It lets the user look at things like text, products, faces, and colors, and the MyEye will attempt to convert what is seen into spoken output.

OCR

The MyEye contains two forms of OCR. The OrCam user can press a button, which will read text aloud to the user. The user can also point at text with their index finger to have OrCam read specific areas on a page.

Products

The MyEye has the ability to scan product bar codes. This will allow the device to identify labeled products, from foods to personal care items and more.

Colors

One of the more interesting features of the MyEye device is the fact that it can detect colors. The user can point at a surface without text to find out what the color is. The spectrum of color that the device can identify is quite extensive compared to Seeing AI.

Faces

The OrCam MyEye lets a user take a picture of a person’s face. Once this is done, the MyEye can determine which faces are in the room. This feature does require the person to record the name of the displayed face beforehand.

Summary

The MyEye from OrCam is a great device for accurate OCR. It is a stand alone device, and works really well. The downside:  The price comes in at over $3000 for the MyEye, and $2000 for the MyReader, which only supports OCR features.

Seeing AI from Microsoft

Seeing AI is an app in the iOS app store that lets users complete many of the same tasks as the OrCam MyEye, but with a few differences.

Short Text OCR

Seeing AI has a fascinating mode called short text, which will let the user read anything visible in the camera’s view. This also means that the app will reset speech if the text is moved to much out of the viewfinder, causing some frustration for users. However, this mode is extremely speedy and accurate, allowing a user to go through a large volume of small documents, like mail, rapidly.

Document OCR

The document channel lets the user scan traditional, longer, documents into Seeing AI for reading or saving. One must simply hold the page near the camera to scan a document. Seeing AI will help you align the document before it scans a page. It will ask the user to hold still once they have aligned the page properly, and it will take the picture. Some users have found, though, that the document recognition is not as good as the short text mode or other apps.

Product

Like the OrCam MyEye, the Seeing AI app lets users scan bar codes. The difference here is that Seeing AI pulls its product data from an online resource. The app provides tone feedback to allow the user to bring the barcode into focus before scanning. The picture is automatically taken at the proper time.

Facial Recognition

Seeing AI will let the user detect a person’s face after pictures have been taken and recorded in the app of that person. Seeing AI will also tell you information about the person, and of how many people are in the viewfinder. The downside to this feature is that the information provided, such as age and gender, is not always accurate, but Microsoft is still making improvements to the app.

Scene (Beta)

One of the most interesting features of Seeing AI is the scene channel of the app, which lets the user know what is in the immediate environment. Keep in mind when you use this channel, that it may not be the most accurate, since it is in beta.

Currency Reader (Beta)

Seeing AI will let the user read various currencies. Simply put the currency under the camera, and Seeing AI will automatically recognize it.

Color (Beta)

Seeing AI now comes with a color detection mode. It basically only recognizes primary colors at this point, but is effective

Handwriting (Beta)

Seeing Ai has an amazing new feature called Handwriting. This channel lets the user scan handwritten text and Seeing AI will read it out loud. This has been the best handwriting scanning I have personally seen in an app.

Light detection

Seeing AI’s last channel is the ability to detect the amount of light that is in a room. Users will hear a lower pitch tone for low light, and a higher tone for bright light.

Conclusion

The OrCam MyEye is an amazing portable device that works on its own without the need for a smartphone. While the services offered are great, I find the $3000 price tag to be a bit steep compared to the free price tag of Seeing AI. I would also have to say that OrCam provides a standard user experience while Seeing AI can vary based on which device the user is using. With that said, Seeing AI does offer more services with the light detection, handwriting, currency and scene channels. If you are looking for a stand alone device, and money is not an issue, then OrCam is right for you, but I think most users will find that Seeing Ai provides similar functionalities built right into the device they carry with them every day. I personally just wish that Seeing AI would make its way to Android.

from Product Comparison: OrCam VS Seeing A.I.

[joejstrickl]

CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice

‘Mirror, mirror on the wall—who’s the fairest in the exhibit hall?’ Beauty brands are once again out in force at CES 2018, with many at CES Unveiled, harnessing cutting-edge technology to make personal care even more personal—and smart.

A year ago at CES, global beauty leader L’Oréal made headlines by announcing the world’s first smart hairbrush, offering a data-driven method to produce better brushing, and haircare, that was billed as the Kérastase Hair Coach Powered by Withings and won a CES innovation award.

Once again proving that being a geek is chic, L’Oréal is back at CES, harnessing its R&D expertise to transform beauty routines—as it has done for decades. Having developed of the first commercial sunscreen in 1935, L’Oréal is honoring its 80-year heritage of sun safety by debuting UV Sense at CES 2018, which marks its first foray into wearable tech.

The battery-free electronic UV sensor (at top) is a tiny patch that you can stick on your finger nail. It’s NFC-enabled so you can scan it with your phone to retrieve the UV data it’s collected, and will work with both Android and iOS phones. It’s less than two millimeters thick and nine millimeters in diameter, and can be worn for up to two weeks on (preferably) a thumbnail—of any gender.

It’s being released with the award-winning My UV Patch. Both products offer consumers critical UV safety information and will be available from La Roche-Posay, L’Oréal’s leading dermatological skincare, brand later this year.

La Roche-Posay has given away more than one million of the My UV Patch stretchable skin sensor monitors to consumers in 37 countries since 2016. Now updating its original patch, the improved UV Sense sensor enables deeper monitoring of UV exposure, storing up to three months of data at a time to show sun damage over time with real-time updates. While not replacing a dermatologist, it augments a healthy skin care routine and keeps the user engaged in his or her skin health.

“L’Oréal research shows that overexposure to UV rays is a top health and beauty concern of consumers worldwide,” stated Guive Balooch, Global Vice President of L’Oréal’s Technology Incubator, in a CES 2018 press release. “With this knowledge, we set out to create something that blends problem-solving technology with human-centered design to reach even more consumers who require additional information about their UV exposure. Whenever we develop a new technology, our goal is to make an enormous global impact by enhancing consumers’ lives.”

Johnson & Johnson’s Neutrogena is at CES to demonstrate its branded skincare tech: Neutrogena Skin360 and SkinScanner, powered by FitSkin. The goal is to demystify skincare by tracking consumers’ skin health while providing personalized skincare advice.

The Skin360 app and SkinScanner tool that work together to measure what’s happening below the skin’s surface. They can track pores, fine lines, wrinkles and moisture levels. Each scan generates a Skin360 Score, offering analysis with a recommended skin care routine and products best suited unique to the user’s skin type and issues.

“Shopping for skincare products can be an overwhelming and confusing experience for our consumer because she is uncertain about what her skin really needs,” said Sebastien Guillon, Global President of Beauty, Johnson & Johnson Consumer, in a CES press release. “Smart and connected technology helps us provide our consumer with personalized analyses and information she needs in real time so she can make decisions that will help her achieve her best skin ever.”

The SkinScanner tool fits over a smartphone and is built with 12 high-powered lights, a 30x magnification lens, and highly-accurate sensors to capture the size and appearance of pores; the size and depth of fine lines and wrinkles; and measures the skin’s moisture levels.

The Neutrogena Skin360 app and SkinScanner tool will be available later this year for $49.99 exclusively via Neutrogena.com.

Made in Taiwan, HiMirror has been named a CES 2018 Innovation Awards Honoree for its HiMirror Mini, which will be available in the U.S. by September. It’s being called the first voice-activated smart mirror, and also offers personalized skincare analysis based on the condition of the user’s skin, local weather conditions and more.

To make looking in the mirror productive for the mind and body, HiMirror features an entertainment center with news stories, music, ambient make up lighting, video tutorials and a virtual make up feature and a mobile app lets users track and tweak skincare on the go.

HiMirror keeps an ongoing record of the user’s skin to track goals and the results of products used, so it’s not wedded to a particular brand of beauty products. It also allows users to provide feedback on products used efficacy. A user’s collection of skincare products can be scanned into the system through a virtual “My Beauty Box” by barcode, with reminders sent for any product expirations.

Priced at $249 and approximately 13.31 x 9.02 inches, with a 10.1″ TFT LCD panel adjustable for optimal and accurate lighting, the HiMirror Mini is equipped with Amazon Alexa-enabled features, privacy facial and voice recognition account access and a noise cancellation microphone.

“HiMirror is a technology-driven beauty tool and one of the first in its market to truly revolutionize the modern beauty routine,” said Simon Shen, CEO of Taipei-based New Kinpo Group. “We know consumers will make HiMirror and its accessories an essential part of their beauty and wellness regimen and we are excited to add the more portable and easy-to-use HiMirror Mini to our already outstanding product portfolio.”

#CESUnveiled Meet the personal skin cares @romy_paris #CES2018 pic.twitter.com/Zwpg7t99sy

— Maxime (@maxsab) January 8, 2018

In other beauty products at CES, Romy Paris is promoting its ‘miniaturized laboratory’ that creates a personalized skin care serum daily along with a beauty coaching app that takes your environment, activities, and sleep habits into consideration. The $800 ‘cosmetic formulator’ and personal cosmetics lab uses technology similar to the cold extraction used in a juicer and a multi-user mode creates individual serums for different people in the household.

#CESUnveiled is officially opened ! Come and meet our co-founder Morgan Acas ! #ces #ces2018 pic.twitter.com/eaAcHj6WHh

— Romy Paris (@romy_paris) January 8, 2018

Kohler is showcasing its Verdera Voice Lighted Mirror, starting at $999. Voice-enabled with Amazon Alexa, a user can stream music, get weather updates and use voice commands to control lighting, and for night, works as a motion-activated night light that brightens for handwashing.

Schwarzkopf Professional says its SalonLab tool is a ‘game-changer in hair analysis.’ The SalonLab handheld device measures inner hair condition and moisture level and even identify true hair color. An accompanying app is AR-ready to virtually see how different hair colors look.

Age-defying and beauty-enhancing, the market for smart products that give Mother Nature a little help is just beginning to mature.

The post CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice appeared first on brandchannel:.

[glenmenlow]

CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice

‘Mirror, mirror on the wall—who’s the fairest in the exhibit hall?’ Beauty brands are once again out in force at CES 2018, with many at CES Unveiled, harnessing cutting-edge technology to make personal care even more personal—and smart.

A year ago at CES, global beauty leader L’Oréal made headlines by announcing the world’s first smart hairbrush, offering a data-driven method to produce better brushing, and haircare, that was billed as the Kérastase Hair Coach Powered by Withings and won a CES innovation award.

Once again proving that being a geek is chic, L’Oréal is back at CES, harnessing its R&D expertise to transform beauty routines—as it has done for decades. Having developed of the first commercial sunscreen in 1935, L’Oréal is honoring its 80-year heritage of sun safety by debuting UV Sense at CES 2018, which marks its first foray into wearable tech.

The battery-free electronic UV sensor (at top) is a tiny patch that you can stick on your finger nail. It’s NFC-enabled so you can scan it with your phone to retrieve the UV data it’s collected, and will work with both Android and iOS phones. It’s less than two millimeters thick and nine millimeters in diameter, and can be worn for up to two weeks on (preferably) a thumbnail—of any gender.

It’s being released with the award-winning My UV Patch. Both products offer consumers critical UV safety information and will be available from La Roche-Posay, L’Oréal’s leading dermatological skincare, brand later this year.

La Roche-Posay has given away more than one million of the My UV Patch stretchable skin sensor monitors to consumers in 37 countries since 2016. Now updating its original patch, the improved UV Sense sensor enables deeper monitoring of UV exposure, storing up to three months of data at a time to show sun damage over time with real-time updates. While not replacing a dermatologist, it augments a healthy skin care routine and keeps the user engaged in his or her skin health.

“L’Oréal research shows that overexposure to UV rays is a top health and beauty concern of consumers worldwide,” stated Guive Balooch, Global Vice President of L’Oréal’s Technology Incubator, in a CES 2018 press release. “With this knowledge, we set out to create something that blends problem-solving technology with human-centered design to reach even more consumers who require additional information about their UV exposure. Whenever we develop a new technology, our goal is to make an enormous global impact by enhancing consumers’ lives.”

Johnson & Johnson’s Neutrogena is at CES to demonstrate its branded skincare tech: Neutrogena Skin360 and SkinScanner, powered by FitSkin. The goal is to demystify skincare by tracking consumers’ skin health while providing personalized skincare advice.

The Skin360 app and SkinScanner tool that work together to measure what’s happening below the skin’s surface. They can track pores, fine lines, wrinkles and moisture levels. Each scan generates a Skin360 Score, offering analysis with a recommended skin care routine and products best suited unique to the user’s skin type and issues.

“Shopping for skincare products can be an overwhelming and confusing experience for our consumer because she is uncertain about what her skin really needs,” said Sebastien Guillon, Global President of Beauty, Johnson & Johnson Consumer, in a CES press release. “Smart and connected technology helps us provide our consumer with personalized analyses and information she needs in real time so she can make decisions that will help her achieve her best skin ever.”

The SkinScanner tool fits over a smartphone and is built with 12 high-powered lights, a 30x magnification lens, and highly-accurate sensors to capture the size and appearance of pores; the size and depth of fine lines and wrinkles; and measures the skin’s moisture levels.

The Neutrogena Skin360 app and SkinScanner tool will be available later this year for $49.99 exclusively via Neutrogena.com.

Made in Taiwan, HiMirror has been named a CES 2018 Innovation Awards Honoree for its HiMirror Mini, which will be available in the U.S. by September. It’s being called the first voice-activated smart mirror, and also offers personalized skincare analysis based on the condition of the user’s skin, local weather conditions and more.

To make looking in the mirror productive for the mind and body, HiMirror features an entertainment center with news stories, music, ambient make up lighting, video tutorials and a virtual make up feature and a mobile app lets users track and tweak skincare on the go.

HiMirror keeps an ongoing record of the user’s skin to track goals and the results of products used, so it’s not wedded to a particular brand of beauty products. It also allows users to provide feedback on products used efficacy. A user’s collection of skincare products can be scanned into the system through a virtual “My Beauty Box” by barcode, with reminders sent for any product expirations.

Priced at $249 and approximately 13.31 x 9.02 inches, with a 10.1″ TFT LCD panel adjustable for optimal and accurate lighting, the HiMirror Mini is equipped with Amazon Alexa-enabled features, privacy facial and voice recognition account access and a noise cancellation microphone.

“HiMirror is a technology-driven beauty tool and one of the first in its market to truly revolutionize the modern beauty routine,” said Simon Shen, CEO of Taipei-based New Kinpo Group. “We know consumers will make HiMirror and its accessories an essential part of their beauty and wellness regimen and we are excited to add the more portable and easy-to-use HiMirror Mini to our already outstanding product portfolio.”

#CESUnveiled Meet the personal skin cares @romy_paris #CES2018 pic.twitter.com/Zwpg7t99sy

— Maxime (@maxsab) January 8, 2018

https://platform.twitter.com/widgets.js

In other beauty products at CES, Romy Paris is promoting its ‘miniaturized laboratory’ that creates a personalized skin care serum daily along with a beauty coaching app that takes your environment, activities, and sleep habits into consideration. The $800 ‘cosmetic formulator’ and personal cosmetics lab uses technology similar to the cold extraction used in a juicer and a multi-user mode creates individual serums for different people in the household.

#CESUnveiled is officially opened ! Come and meet our co-founder Morgan Acas ! #ces #ces2018 pic.twitter.com/eaAcHj6WHh

— Romy Paris (@romy_paris) January 8, 2018

https://platform.twitter.com/widgets.js

Kohler is showcasing its Verdera Voice Lighted Mirror, starting at $999. Voice-enabled with Amazon Alexa, a user can stream music, get weather updates and use voice commands to control lighting, and for night, works as a motion-activated night light that brightens for handwashing.

Schwarzkopf Professional says its SalonLab tool is a ‘game-changer in hair analysis.’ The SalonLab handheld device measures inner hair condition and moisture level and even identify true hair color. An accompanying app is AR-ready to virtually see how different hair colors look.

Age-defying and beauty-enhancing, the market for smart products that give Mother Nature a little help is just beginning to mature.

The post CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice appeared first on brandchannel:.

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CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice

‘Mirror, mirror on the wall—who’s the fairest in the exhibit hall?’ Beauty brands are once again out in force at CES 2018, with many at CES Unveiled, harnessing cutting-edge technology to make personal care even more personal—and smart.

A year ago at CES, global beauty leader L’Oréal made headlines by announcing the world’s first smart hairbrush, offering a data-driven method to produce better brushing, and haircare, that was billed as the Kérastase Hair Coach Powered by Withings and won a CES innovation award.

Once again proving that being a geek is chic, L’Oréal is back at CES, harnessing its R&D expertise to transform beauty routines—as it has done for decades. Having developed of the first commercial sunscreen in 1935, L’Oréal is honoring its 80-year heritage of sun safety by debuting UV Sense at CES 2018, which marks its first foray into wearable tech.

The battery-free electronic UV sensor (at top) is a tiny patch that you can stick on your finger nail. It’s NFC-enabled so you can scan it with your phone to retrieve the UV data it’s collected, and will work with both Android and iOS phones. It’s less than two millimeters thick and nine millimeters in diameter, and can be worn for up to two weeks on (preferably) a thumbnail—of any gender.

It’s being released with the award-winning My UV Patch. Both products offer consumers critical UV safety information and will be available from La Roche-Posay, L’Oréal’s leading dermatological skincare, brand later this year.

La Roche-Posay has given away more than one million of the My UV Patch stretchable skin sensor monitors to consumers in 37 countries since 2016. Now updating its original patch, the improved UV Sense sensor enables deeper monitoring of UV exposure, storing up to three months of data at a time to show sun damage over time with real-time updates. While not replacing a dermatologist, it augments a healthy skin care routine and keeps the user engaged in his or her skin health.

“L’Oréal research shows that overexposure to UV rays is a top health and beauty concern of consumers worldwide,” stated Guive Balooch, Global Vice President of L’Oréal’s Technology Incubator, in a CES 2018 press release. “With this knowledge, we set out to create something that blends problem-solving technology with human-centered design to reach even more consumers who require additional information about their UV exposure. Whenever we develop a new technology, our goal is to make an enormous global impact by enhancing consumers’ lives.”

Johnson & Johnson’s Neutrogena is at CES to demonstrate its branded skincare tech: Neutrogena Skin360 and SkinScanner, powered by FitSkin. The goal is to demystify skincare by tracking consumers’ skin health while providing personalized skincare advice.

The Skin360 app and SkinScanner tool that work together to measure what’s happening below the skin’s surface. They can track pores, fine lines, wrinkles and moisture levels. Each scan generates a Skin360 Score, offering analysis with a recommended skin care routine and products best suited unique to the user’s skin type and issues.

“Shopping for skincare products can be an overwhelming and confusing experience for our consumer because she is uncertain about what her skin really needs,” said Sebastien Guillon, Global President of Beauty, Johnson & Johnson Consumer, in a CES press release. “Smart and connected technology helps us provide our consumer with personalized analyses and information she needs in real time so she can make decisions that will help her achieve her best skin ever.”

The SkinScanner tool fits over a smartphone and is built with 12 high-powered lights, a 30x magnification lens, and highly-accurate sensors to capture the size and appearance of pores; the size and depth of fine lines and wrinkles; and measures the skin’s moisture levels.

The Neutrogena Skin360 app and SkinScanner tool will be available later this year for $49.99 exclusively via Neutrogena.com.

Made in Taiwan, HiMirror has been named a CES 2018 Innovation Awards Honoree for its HiMirror Mini, which will be available in the U.S. by September. It’s being called the first voice-activated smart mirror, and also offers personalized skincare analysis based on the condition of the user’s skin, local weather conditions and more.

To make looking in the mirror productive for the mind and body, HiMirror features an entertainment center with news stories, music, ambient make up lighting, video tutorials and a virtual make up feature and a mobile app lets users track and tweak skincare on the go.

HiMirror keeps an ongoing record of the user’s skin to track goals and the results of products used, so it’s not wedded to a particular brand of beauty products. It also allows users to provide feedback on products used efficacy. A user’s collection of skincare products can be scanned into the system through a virtual “My Beauty Box” by barcode, with reminders sent for any product expirations.

Priced at $249 and approximately 13.31 x 9.02 inches, with a 10.1″ TFT LCD panel adjustable for optimal and accurate lighting, the HiMirror Mini is equipped with Amazon Alexa-enabled features, privacy facial and voice recognition account access and a noise cancellation microphone.

“HiMirror is a technology-driven beauty tool and one of the first in its market to truly revolutionize the modern beauty routine,” said Simon Shen, CEO of Taipei-based New Kinpo Group. “We know consumers will make HiMirror and its accessories an essential part of their beauty and wellness regimen and we are excited to add the more portable and easy-to-use HiMirror Mini to our already outstanding product portfolio.”

#CESUnveiled Meet the personal skin cares @romy_paris #CES2018 http://pic.twitter.com/Zwpg7t99sy

— Maxime (@maxsab) January 8, 2018

In other beauty products at CES, Romy Paris is promoting its ‘miniaturized laboratory’ that creates a personalized skin care serum daily along with a beauty coaching app that takes your environment, activities, and sleep habits into consideration. The $800 ‘cosmetic formulator’ and personal cosmetics lab uses technology similar to the cold extraction used in a juicer and a multi-user mode creates individual serums for different people in the household.

#CESUnveiled is officially opened ! Come and meet our co-founder Morgan Acas ! #ces #ces2018 http://pic.twitter.com/eaAcHj6WHh

— Romy Paris (@romy_paris) January 8, 2018

Kohler is showcasing its Verdera Voice Lighted Mirror, starting at $999. Voice-enabled with Amazon Alexa, a user can stream music, get weather updates and use voice commands to control lighting, and for night, works as a motion-activated night light that brightens for handwashing.

Schwarzkopf Professional says its SalonLab tool is a ‘game-changer in hair analysis.’ The SalonLab handheld device measures inner hair condition and moisture level and even identify true hair color. An accompanying app is AR-ready to virtually see how different hair colors look.

Age-defying and beauty-enhancing, the market for smart products that give Mother Nature a little help is just beginning to mature.

The post CES 2018: Beauty Brands Get Personal With Wearable Tech, AR and Voice appeared first on brandchannel:.