{"id":"https://openalex.org/W3201639474","doi":"https://doi.org/10.1142/s0218001421600120","title":"Impact of Labeling Schemes on Dense Crowd Counting Using Convolutional Neural Networks with Multiscale Upsampling","display_name":"Impact of Labeling Schemes on Dense Crowd Counting Using Convolutional Neural Networks with Multiscale Upsampling","publication_year":2021,"publication_date":"2021-09-15","ids":{"openalex":"https://openalex.org/W3201639474","doi":"https://doi.org/10.1142/s0218001421600120","mag":"3201639474"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001421600120","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s0218001421600120","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1142/s0218001421600120","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078309302","display_name":"Greg Olmschenk","orcid":"https://orcid.org/0000-0001-8472-2219"},"institutions":[{"id":"https://openalex.org/I121847817","display_name":"The Graduate Center, CUNY","ror":"https://ror.org/00awd9g61","country_code":"US","type":"education","lineage":["https://openalex.org/I121847817"]},{"id":"https://openalex.org/I1306266525","display_name":"Goddard Space Flight Center","ror":"https://ror.org/0171mag52","country_code":"US","type":"facility","lineage":["https://openalex.org/I1306266525","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Greg Olmschenk","raw_affiliation_strings":["Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA","NASA Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA","institution_ids":["https://openalex.org/I121847817"]},{"raw_affiliation_string":"NASA Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA","institution_ids":["https://openalex.org/I1306266525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329006","display_name":"Xuan Wang","orcid":"https://orcid.org/0000-0002-6266-1387"},"institutions":[{"id":"https://openalex.org/I121847817","display_name":"The Graduate Center, CUNY","ror":"https://ror.org/00awd9g61","country_code":"US","type":"education","lineage":["https://openalex.org/I121847817"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xuan Wang","raw_affiliation_strings":["Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA","institution_ids":["https://openalex.org/I121847817"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101745105","display_name":"Hao Tang","orcid":"https://orcid.org/0000-0002-6197-0874"},"institutions":[{"id":"https://openalex.org/I15653065","display_name":"Borough of Manhattan Community College","ror":"https://ror.org/040hwr020","country_code":"US","type":"education","lineage":["https://openalex.org/I15653065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Tang","raw_affiliation_strings":["Department of Computer Information Systems, Borough of Manhattan Community College, CUNY, 199 Chambers Street, New York, NY 10007, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Information Systems, Borough of Manhattan Community College, CUNY, 199 Chambers Street, New York, NY 10007, USA","institution_ids":["https://openalex.org/I15653065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088347883","display_name":"Zhigang Zhu","orcid":"https://orcid.org/0000-0002-9990-1137"},"institutions":[{"id":"https://openalex.org/I121847817","display_name":"The Graduate Center, CUNY","ror":"https://ror.org/00awd9g61","country_code":"US","type":"education","lineage":["https://openalex.org/I121847817"]},{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhigang Zhu","raw_affiliation_strings":["Department of Computer Science, The City College of New York, CUNY, 160 Convent Avenue, New York, NY 10031, USA","Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The City College of New York, CUNY, 160 Convent Avenue, New York, NY 10031, USA","institution_ids":["https://openalex.org/I125687163"]},{"raw_affiliation_string":"Department of Computer Science, The Graduate Center, CUNY, 365 Fifth Avenue, New York, NY 10016, USA","institution_ids":["https://openalex.org/I121847817"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5078309302","https://openalex.org/A5100329006"],"corresponding_institution_ids":["https://openalex.org/I121847817","https://openalex.org/I1306266525"],"apc_list":null,"apc_paid":null,"fwci":0.2913,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56453385,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"35","issue":"16","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7170255780220032},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7074735760688782},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6765217781066895},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.613387405872345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5372320413589478},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4629806578159332},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4327285885810852},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41529619693756104}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7170255780220032},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074735760688782},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6765217781066895},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.613387405872345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5372320413589478},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4629806578159332},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4327285885810852},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41529619693756104},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001421600120","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s0218001421600120","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1142/s0218001421600120","is_oa":true,"landing_page_url":"https://doi.org/10.1142/s0218001421600120","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1595963390","display_name":null,"funder_award_id":"1827505","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4070137553","display_name":null,"funder_award_id":"HHM402-18-1-0007","funder_id":"https://openalex.org/F4320312530","funder_display_name":"Office of the Director of National Intelligence"},{"id":"https://openalex.org/G5467036517","display_name":null,"funder_award_id":"HHM402-19-1-0003","funder_id":"https://openalex.org/F4320312530","funder_display_name":"Office of the Director of National Intelligence"},{"id":"https://openalex.org/G8569551686","display_name":null,"funder_award_id":"1737533","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1910776219","https://openalex.org/W1976959044","https://openalex.org/W2013039598","https://openalex.org/W2072232009","https://openalex.org/W2075875861","https://openalex.org/W2123175289","https://openalex.org/W2138948290","https://openalex.org/W2194775991","https://openalex.org/W2293078015","https://openalex.org/W2463631526","https://openalex.org/W2520723410","https://openalex.org/W2596585349","https://openalex.org/W2741077351","https://openalex.org/W2798489385","https://openalex.org/W2798490576","https://openalex.org/W2883929025","https://openalex.org/W2884960332","https://openalex.org/W2886443245","https://openalex.org/W2895051362","https://openalex.org/W2922282711","https://openalex.org/W2962720716","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964209782","https://openalex.org/W2995582330","https://openalex.org/W3034785991"],"related_works":["https://openalex.org/W4240200267","https://openalex.org/W2062399876","https://openalex.org/W1511510665","https://openalex.org/W2154955495","https://openalex.org/W1524661185","https://openalex.org/W2078823605","https://openalex.org/W2500095415","https://openalex.org/W2097922264","https://openalex.org/W1997780040","https://openalex.org/W2282342021"],"abstract_inverted_index":{"Gatherings":[0],"of":[1,5,13,23,35,49,121,147,173,183,191,245],"thousands":[2],"to":[3,117,169],"millions":[4],"people":[6],"frequently":[7],"occur":[8],"for":[9,29,53],"an":[10,36,67,201],"enormous":[11],"variety":[12],"educational,":[14],"social,":[15],"sporting,":[16],"and":[17,20,32,179,241,243,256],"political":[18],"events,":[19],"automated":[21],"counting":[22,140],"these":[24],"high-density":[25],"crowds":[26],"is":[27],"useful":[28],"safety,":[30],"management,":[31],"measuring":[33],"significance":[34],"event.":[37],"In":[38],"this":[39],"work,":[40],"we":[41,98,198,211],"show":[42,212],"that":[43,97,213],"the":[44,61,122,132,148,158,165,171,180,184,189,205,226,237],"regularly":[45],"accepted":[46],"labeling":[47,152],"scheme":[48],"crowd":[50,139,192,251,254,257],"density":[51,193],"maps":[52,136],"training":[54],"deep":[55],"neural":[56],"networks":[57],"may":[58],"not":[59],"be":[60],"most":[62],"effective":[63],"one.":[64],"We":[65,90,142],"propose":[66],"alternative":[68],"inverse":[69,214],"k-nearest":[70],"neighbor":[71],"(i[Formula:":[72],"see":[73,104,125,134,150,160,207,218,223],"text]NN)":[74,224],"map":[75,220],"mechanism":[76,203],"that,":[77],"even":[78],"when":[79],"used":[80],"directly":[81],"in":[82,100,167,195,204,239],"existing":[83],"state-of-the-art":[84],"network":[85,94,106],"structures,":[86],"shows":[87],"superior":[88],"performance.":[89,228],"also":[91,199],"provide":[92],"new":[93],"architecture":[95],"mechanisms":[96],"demonstrate":[99],"our":[101],"own":[102],"MUD-i[Formula:":[103],"text]NN":[105,126,135,151,161,208,219],"architecture,":[107],"which":[108,154],"uses":[109],"multi-scale":[110],"drop-in":[111],"replacement":[112],"upsampling":[113,129],"via":[114],"transposed":[115],"convolutions":[116],"take":[118],"full":[119],"advantage":[120],"provided":[123,231],"i[Formula:":[124,133,149,206],"labeling.":[127],"This":[128],"combined":[130],"with":[131],"further":[137,143],"improves":[138],"accuracy.":[141],"analyze":[144],"several":[145],"variations":[146],"mechanism,":[153],"apply":[155],"transformations":[156],"on":[157,232],"[Formula:":[159,217],"measure":[162],"before":[163],"generating":[164],"map,":[166],"order":[168],"consider":[170],"impact":[172],"camera":[174],"perspective":[175],"views,":[176],"image":[177],"resolutions,":[178,236],"changing":[181],"rates":[182],"mapping":[185,240],"functions.":[186],"To":[187],"alleviate":[188],"effects":[190],"changes":[194],"each":[196],"image,":[197],"introduce":[200],"attenuation":[202],"mapping.":[209],"Experimentally,":[210],"square":[215],"root":[216],"variation":[221],"(iR[Formula:":[222],"provides":[225],"best":[227],"Discussions":[229],"are":[230],"computational":[233],"complexity,":[234],"label":[235],"gains":[238],"upsampling,":[242],"details":[244],"critical":[246],"cases":[247],"such":[248],"as":[249],"various":[250],"counts,":[252],"uneven":[253],"densities,":[255],"occlusions.":[258]},"counts_by_year":[{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}