#maxtree

[maxtree-cgi]

Plant Models Vol 153

This is a collection of small-leaved shrub plants that grow in river valleys, hillsides, rocky areas, forest edges, and alpine shrub meadows. Their characteristics include cold hardiness, drought tolerance, and a preference for sunlight. Of course, they can also be used for other scenes and would be quite beautiful.

25% discount until Aug 8th.

[alphatree]

Automatic built-up detection using the CSL (characteristic-scale, saliency, level) semantic triplet.

The CSL is the result of the structured collapse of a differential area profile vector field computed from the max-tree data structure of a radiometrically reduced image. The example shows a section of Seattle (WA). More on https://lnkd.in/emYcWAB and https://lnkd.in/eRiAUZV

[robovis]

hyper-connected motion detection pattern analytics

The volume set on the top shows a raw motion detection sequence computed using an algorithm based on mixture of Gaussians (MoG) on a feed from a motion-activated security camera. Detections correspond to two people dancing and the feed is several minutes long. The signal is buried in noise caused by the detection algorithm, by the compression algorithm, and by dynamic contrast recalibration (the feed is from a night capture).

The middle set shows the result of a 3D connected attribute filter using non-compactness as a criterion. The filter is configured with second-generation mask-based connectivity that clusters signal fragments in the time dimension strictly. The signal is boosted but a large percentage of noise remains.

The lower set shows the effect of enabling the hyper-connectivity parameter k that neatly absorbs all noise and leaves an uncorrupted signal behind.

The filter operates on 1 sec long segments of the feed, long-enough to discriminate structures based on non-compactness in 30 fps feeds/videos. Detections in subsequent time-space segments (volume sets) are interconnected using the a motion zone summary (superposition of motion detections) of the previous volume set brought at the input of the current. Time-connectivity enables propagating knowledge accumulated from previous sets into the current.

The visualizations above were produced with the Max-Tree demo

For more contact Georgios K. Ouzounis

[paulojacomelli]

Renderização com Blender Cycles Entre em contato: Email: paulojacomelli.design@gmail.com Facebook: facebook.com/paulojacomelli.design Instagram: instagram.com/paulo.jacomelli WhatsApp: https://api.whatsapp.com/send?phone=5517988211306 Site http://paulojacomellidesign.blogspot.com #blender #b3d #3drendering #blender3d #blendercycles #3dmodeling #archiviz #archiviz3d #maxtree #quixel #quixelmegascans #bridge #cgi #computergraphics #render #rendering3d #blenderrender #cyclesrender #arquitetura #renderização #modelagem3d #computaçãográfica #blenderparaarquitetura #blendercommunity #render #fotorealismo #photorealism #arquitectura #maqueteeletronica #blenderkit #coreweave (em Catanduva, São Paulo) https://www.instagram.com/p/B-5kF8dD4PM/?igshid=ubgrbn8nh6ml

[myworldofelegance]

Ronald Van Der Kemp Fall 2019 Haute Couture

source:TheImpression.com

Photo//maxtree

[mpviz]

CG House I Interior @mpassosviz More in www.matheuspassos.com #3d #3dartist #vray #3dsmax #brazilianarchitecture #arquiteturabrasileira #movelbrasileiro #brazilianfurniture #fazendaboavista #landscape #growfx #vizpark #maxtree #maqueteeletronica #oculusgo #oculusgobrasil #vr #coralgables #GODisGOOD @chaosgroup @maxtree_studio @vizpark @designconnected @extreme_textures @itoosoftware https://ift.tt/2vHCKNc

[maxtree-cgi]

Plant Models Vol 152 - Australian Plants.

Plant Models Vol 152 is now released-Australian Plants.

They are diverse in form, and I believe they can make your scene shine.

25% discount until July 26th.

[alphatree]

maxtree attribute filters for remote sensing

An example of a size & shape sensitive attribute filter for search space reduction in building footprint detection using the maxtree algorithm.

[robovis]

Motion Detection

Examples of motion detection using the next big thingf, the maxtree algorithm along with Differential Short-Term Memory buffers, on motion activation security camera feeds.

For more contact Georgos K. Ouzounis

[adaz3d]

MAXTREE Plant Models Vol 38

MAXTREE Plant Models Vol 38 MAX | FBX | OBJ | TEX | 3D Models | 2 GB

source https://www.adaz3d.com/graphic/3dmodel/6098-maxtree-plant-models-vol-38.html

[nhandyjr]

Predicting Political Party Membership using Outlook-On-Life Survey and Random Forest

TASK:

Random forest analysis was performed to evaluate the importance of a series of survey questions (primarily pertaining to U. S. social attitudes) in predicting a binary, categorical response variable, Tea Party Membership at the time of the Outlook-On-Life Survey (OOL) in 2012.  

  MODEL APPROACH:

Nearly 60 economic and social attitude questions served as possible explanatory variables in classification of responses to the question, "Tea Party Membership."  OOL questions pertaining to economic status, optimism for relationship prospects, personal and inter-generational goal fulfillment; attitudes on inter-racial dating, inequality issues, child-rearing; and personal ratings of racial groups were the focus. Much care was taken to exclude questions pertaining to political parties, groups or individuals related to the target variable  Tea Party Membership (TeaParty_b) by either support or opposition. 

Here are some of the questions of interest:

“How optimistic are you that you will develop a serious and/or marital relationship?” (Optmsm_Rlshp)

Does your household subscribe to a digital cable television service? (DigiCable_b)

“[Increase legal penalties for sexual harassment? ] What is your opinion about each of them?” (IncSHPnlty_10)

“Do you personally, or jointly with a spouse, have any money invested in the stock market right now—either in an individual stock or in a mutual fund?” (StockInv_b)

“How would you rate public school teachers?” (RatePubTch_100)

Do you presently have any kind of health insurance? (HealthIns_b)

“And when you think about the future of the United States as a whole, are you generally optimistic, pessimistic, or neither optimistic nor pessimistic?” (OptmsmUS_Futr)

“[To own a home ] For yourself and people like you, how easy or hard is it to reach these goals?” (HardToOwnHome)

"How do you rate unions?" (RateUnion)  

“[To do better than one’s parents did ] For yourself and people like you, how easy or hard is it to reach these goals?” (HardToBetterParents)

“Have you dated outside of your race?” (DatedOSRace_b)

“Have you had sex with someone outside of your racial group?” (SexOSRace_b)

“Blacks should (overcome prejudice and work their way up(e.g, Irish, Italians, Jews, Others)) without any special favors?” (BlksNoFvrIIJO)

“How do you rate Undocumented Immigrants?” (RateUnDoc)

Results:  

With a classification rate of 98%, ironically, the decision tree version of this model returned classification rates of 100%, 100%, 99.96%, and 99.96% under various growth and pruning parameters.

Under various “in-bag fraction” parameters, we can see the convergence of the misclassification rate to 2%.  From the 9 results, for this particular party, the top 5 variables (survey questions) are listed. The following OOL survey questions appeared as top 5 features 8, 7 and 6 times, respectively:

“Are you a citizen of the United States ?” (USCit_b)

“Society has reached the point where blacks and whites have equal opportunities for achievement.”  (BWEqulOppty)

“Are you extremely [optimistic/pessimistic], moderately [optimistic/pessimistic], or slightly [optimistic/pessimistic] (that you will develop a serious and/or marital relationship)?”  (Optmsm_Rlshp_ntr)

options mprint mlogic symbolgen; ods graphics on; %macro randfor(ds= ,trees=,vartry=,f=,trg=,suff=, asnmiss=); proc hpforest data=&ds maxtrees=&trees vars_to_try=&vartry trainfraction=&f ; target &trg/level=binary; input Optmsm_Rlshp Optmsm_Rlshp_ntr Optmsm_Futr Optmsm_Futr_ntr HardToOwnHome HardToRetire   HardToCollege HardToWealth HardToBetterParents HardChildToOwnHome HardChildToRetire   HardChildWealth HardChildBetPar SexOSRace_ntr BWEqulOppty   BlksLTDeserve   BlksNoFvrIIJO   BlksTryHarder   SlavDiscrmHardForBlks   NoBlkDiscrm   BlkTchFightDisc   BlkTchNotWhite   BlkTchAvdStyp BlkTchCrflPol   TrustPolice   TrustLegal ClassCat ClassFam Sex_Orient/   level=nominal; input WillDateOSRace_b SexOSRace_b DatedOSRace_b BlkEffect_b BlkWomEffect_b USCit_b USCitNat_b LGBTRel_b MilitaryHHAct_b UnionHH_b UnEeHH_b HealthIns_b StockInv_b DigiCable_b/ level=binary; input RateDrmPath_10 BWEqulJust_7 IncSHPnlty_10 RatePplWelf_100 RateNatAm_100 RateLatino_100 RateWhite_100 RateBlk_100 RateAsian_100 RateLGBT_100 RateUnion_100 RateUnEe_100 RateUnWed_100 RateUnDoc_100 RatePubTch_100/ level=interval; ods output FitStatistics = fitstats_f&suff.(rename=(Miscoob=f&suff.)); run; %mend randfor;

%randfor(ds=home.ool_lab,trees=50,vartry=16,f=.9,suff=09,trg=TeaPartyMem_b);

%randfor(ds=home.ool_lab,trees=50,vartry=16,f=.88,suff=088,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.875,suff=0875,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.86,suff=086,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.5,suff=05,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.4,suff=04,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.23,suff=023,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.202,suff=0202,trg=TeaPartyMem_b); %randfor(ds=home.ool_lab,trees=50,vartry=16,f=.2,suff=02,trg=TeaPartyMem_b);

data fitstats; merge fitstats_f0202 fitstats_f02 fitstats_f023 fitstats_f09 fitstats_f0875 fitstats_f086 fitstats_f088 fitstats_f04 fitstats_f05 ; rename Ntrees=Trees; label f09  = "f=09"; label f0875 = "f=0875"; label f088 = "f=088"; label f086 = "f=086"; label f04 = "f=04"; label f0202 = "f=0202"; label f02 = "f=02"; label f05 = "f=05"; label f23 = "f=23"; run;

proc sgplot data=fitstats; title "Misclassification Rate for Various In-Bag Fraction Values"; series x=Trees y=f09/lineattrs=(Color=black)  ; series x=Trees y=f088/lineattrs=(Pattern=MediumDashDotDot Thickness=2); series x=Trees y=f0875/lineattrs=(Pattern=mediumDashdotdot Thickness=2); series x=Trees y=f086/lineattrs=(Pattern=ShortDash Thickness=2); series x=Trees y=f05/lineattrs=(Pattern=LongDash Thickness=3); series x=Trees y=f04/lineattrs=(Pattern=ShortDash Thickness=2); series x=Trees y=f023/lineattrs=(Pattern=ShortDash Thickness=2); series x=Trees y=f0202/lineattrs=(color=black Thickness=2); series x=Trees y=f02/lineattrs=(Pattern=ShortDash Thickness=2);

yaxis label='OOB Misclassification Rate'; run; title;

[myworldofelegance]

Ronald Van Der Kemp Fall 2019 Haute Couture

source:TheImpression.com

Photo//maxtree

[heroturkopro]

Maxtree Plant Models Vol 15

http://www.heroturkopro.com/?p=43626&utm_source=SocialAutoPoster&utm_medium=Social&utm_campaign=Tumblr Maxtree Plant Models Vol 15 - http://www.heroturkopro.com/?p=43626&utm_source=SocialAutoPoster&utm_medium=Social&utm_campaign=Tumblr -

[crypticzzz]

Ironforge Recreated Using Unreal Engine 4

Youtuber and environmental artist Brian Vagie has recreated the Dwarven city of Ironforge in Unreal Engine 4 using megascan, maxtree, handmade assets and custom animations. Recreating game worlds inside Unreal has become very popular in recent years, as we recently saw with Stormwind City, and although these fan recreations are usually not completely true to Blizzard's art style, they make a good example of the high level of detail that the World of Warcraft could have in Unreal Engine 4. Continue reading » source https://www.wowhead.com/news=312736/ironforge-recreated-using-unreal-engine-4

[mpviz]

Boa Vista House VII Arch @felipe_caboclo_arquitetura Eng @lampurengenharia Interior @mpassosviz More in www.matheuspassos.com @fazendaboavista #3d #3dartist #vray #3dsmax #brazilianarchitecture #arquiteturabrasileira #movelbrasileiro #brazilianfurniture #fazendaboavista #landscape #growfx #vizpark #maxtree #maqueteeletronica #oculusgo #oculusgobrasil #vr #GODisGOOD @chaosgroup @maxtree_studio @vizpark @designconnected @extreme_textures @itoosoftware https://ift.tt/2lzUaXi

[maxtree-cgi]

Plant Models Vol 145-Flowers

Plant Models Vol 145 is now released.

This is a new collection of flowering plants, featuring a large tropical perennial from the Philippines called the Showy Medinilla, which has clusters of pink flowers that hang all year round.

It also includes the Barberton Daisy, which grows in gardens around the world, among many others.

There are a total of 180 individual models in the collection.

25% discount until Jan 29th.