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1、UsingDeepLearningandGoogleStreetViewtoEstimatetheDemographicMakeupoftheUSTimnitGebru1,JonathanKrause1,YilunWang；DuyunChen1,JiaDeng]ErezLiebermanAiden'fLiFei-Fei1'StanfordUniversity,353SerraMall,Stanford,CA94305.2UniversityofMichigan,2260HaywardStreet,AnnArbor,Ml48109.3BaylorCollegeofMedicine,1B
2、aylorPlaza,Houston,TX77030.ARiceUniversity,6100MainStreet,Houston,TX77005.TheUnitedStatesspendsmorethan$1BeachyearoninitiativessuchastheAmericanCommunitySurvey(ACS),alabor-intensivedoor-to-doorstudythatmeasuresstatisticsrelatingtorace,gender;education,occupation,unemployment,andotherdemographic
3、factorsAlthoughacomprehensivesourceofdata,thelagbetweendemographicchangesandtheirappearanceintheACScanexceedhalfadecade.Asdigitalimagerybecomesubiquitousandmachinevisiontechniquesimprove,automateddataanalysismayprovideacheaperandfasteralternative.Here,wepresentamethodthatdeterminessocioeconomi
4、ctrendsfrom50millionimagesofstreetscenes,gatheredin200AmericancitiesbyGoogleStreetViewcars.Usingdeeplearning-basedcomputervisiontechniques,wedeterminedthemake,model,andyearofallmotorvehiclesencounteredinparticularneighborhoods.Datafromthiscensusofmotorvehicles,whichenumerated22Mautomobilesintot
5、al(8%ofallautomobilesintheUS),wasusedtoaccuratelyestimateincome,race,education,andvotingpatterns,withsingleprecinctresolution.(TheaverageUSprecinctcontainsapproximately1000people.)Theresultingassociationsaresurprisinglysimpleandpowerful.Forinstance,ifthenumberofsedansencounteredduringa15-minute
6、drivethroughacityishigherthanthenumberofpickuptrucks,thecityislikelytovoteforaDemocratduringthenextPresidentialelection(88%chanee);otherwise,itislikelytovoteRepublican(82%).Ourresultssuggestthatautomatedsystemsformonitoringdemographictrendsmayeffectivelycomplementlabor-intensiveapproaches,witht
7、hepotentialtodetecttrendswithfinespatialresolution,inclosetorealtime.Forthousandsofyears,rulersandpolicymakershavesurveyednationalpopulationsinordertocollectdemographicstatistics.IntheUnitedStates,themostdetailedsuchstudyistheAmer
