{"id":"https://openalex.org/W4321192600","doi":"https://doi.org/10.1109/icce56470.2023.10043547","title":"Crowd Density Estimation using Imperfect Labels","display_name":"Crowd Density Estimation using Imperfect Labels","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4321192600","doi":"https://doi.org/10.1109/icce56470.2023.10043547"},"language":"en","primary_location":{"id":"doi:10.1109/icce56470.2023.10043547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce56470.2023.10043547","pdf_url":null,"source":{"id":"https://openalex.org/S4363607959","display_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101660547","display_name":"Muhammad Asif Khan","orcid":"https://orcid.org/0000-0003-2925-8841"},"institutions":[{"id":"https://openalex.org/I4210092118","display_name":"Qatar Mobility Innovations Center","ror":"https://ror.org/00dgyys91","country_code":"QA","type":"facility","lineage":["https://openalex.org/I4210092118"]},{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Muhammad Asif Khan","raw_affiliation_strings":["Qatar Mobility Innovations Center (QMIC), Qatar University,Doha,Qatar","Qatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qatar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qatar Mobility Innovations Center (QMIC), Qatar University,Doha,Qatar","institution_ids":["https://openalex.org/I4210092118"]},{"raw_affiliation_string":"Qatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I4210092118","https://openalex.org/I60342839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071128215","display_name":"Hamid Menouar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092118","display_name":"Qatar Mobility Innovations Center","ror":"https://ror.org/00dgyys91","country_code":"QA","type":"facility","lineage":["https://openalex.org/I4210092118"]},{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Hamid Menouar","raw_affiliation_strings":["Qatar Mobility Innovations Center (QMIC), Qatar University,Doha,Qatar","Qatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qatar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qatar Mobility Innovations Center (QMIC), Qatar University,Doha,Qatar","institution_ids":["https://openalex.org/I4210092118"]},{"raw_affiliation_string":"Qatar Mobility Innovations Center (QMIC), Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I4210092118","https://openalex.org/I60342839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073330071","display_name":"Ridha Hamila","orcid":"https://orcid.org/0000-0002-6920-7371"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Ridha Hamila","raw_affiliation_strings":["Qatar University,Electrical Engineering,Doha,Qatar","Electrical Engineering, Qatar University, Doha, Qatar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qatar University,Electrical Engineering,Doha,Qatar","institution_ids":["https://openalex.org/I60342839"]},{"raw_affiliation_string":"Electrical Engineering, Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I60342839"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5261,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.61157718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9991999864578247,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8420780897140503},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7832334041595459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7338683605194092},{"id":"https://openalex.org/keywords/imperfect","display_name":"Imperfect","score":0.6887553334236145},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6664749383926392},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6393053531646729},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4755149483680725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4558585286140442},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37125349044799805}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8420780897140503},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7832334041595459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7338683605194092},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.6887553334236145},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6664749383926392},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6393053531646729},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4755149483680725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4558585286140442},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37125349044799805},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icce56470.2023.10043547","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce56470.2023.10043547","pdf_url":null,"source":{"id":"https://openalex.org/S4363607959","display_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"},{"id":"pmh:oai:qspace.qu.edu.qa:10576/41637","is_oa":false,"landing_page_url":"http://hdl.handle.net/10576/41637","pdf_url":null,"source":{"id":"https://openalex.org/S4306400014","display_name":"Qatar University QSpace (Qatar University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I60342839","host_organization_name":"Qatar University","host_organization_lineage":["https://openalex.org/I60342839"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G3582672085","display_name":null,"funder_award_id":"PDRA7-0606-21012","funder_id":"https://openalex.org/F4320332753","funder_display_name":"Qatar National Research Fund"}],"funders":[{"id":"https://openalex.org/F4320332753","display_name":"Qatar National Research Fund","ror":"https://ror.org/01svaqq28"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1910776219","https://openalex.org/W2097117768","https://openalex.org/W2194775991","https://openalex.org/W2463631526","https://openalex.org/W2517615595","https://openalex.org/W2586716774","https://openalex.org/W2741077351","https://openalex.org/W2895051362","https://openalex.org/W2962720716","https://openalex.org/W2962921175","https://openalex.org/W2964209782","https://openalex.org/W2967069910","https://openalex.org/W2969620138","https://openalex.org/W2976931991","https://openalex.org/W2982509888","https://openalex.org/W3047585969","https://openalex.org/W3110089972","https://openalex.org/W3176047859","https://openalex.org/W3179212946","https://openalex.org/W3189255654","https://openalex.org/W4290997080","https://openalex.org/W4309903996","https://openalex.org/W4312880818","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6766285325","https://openalex.org/W6767489048","https://openalex.org/W6843470407"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2378211422","https://openalex.org/W2374250903","https://openalex.org/W2358755282","https://openalex.org/W2745001401","https://openalex.org/W4321353415"],"abstract_inverted_index":{"Density":[0],"estimation":[1],"is":[2,39],"one":[3],"of":[4,36,45,63,75,80,94,156,165],"the":[5,33,37,43,46,78,84,92,148,157],"most":[6],"widely":[7],"used":[8,125],"method":[9],"for":[10],"crowd":[11,23,27,67,103,130,139,166],"counting":[12,56,68,104,131,140],"in":[13,29],"which":[14,122],"a":[15,108,116,128],"deep":[16,117],"learning":[17,34,118],"model":[18,38,85,119,132,158],"learns":[19],"from":[20],"head":[21],"annotated":[22],"images":[24],"to":[25,53,126,154,168],"estimate":[26],"density":[28],"unseen":[30],"images.":[31],"Typically,":[32],"performance":[35],"highly":[40],"impacted":[41],"by":[42],"accuracy":[44,152],"annotations":[47,50],"and":[48,55,99,142],"inaccurate":[49],"may":[51],"lead":[52],"localization":[54],"errors":[57,82],"during":[58],"prediction.":[59],"A":[60],"significant":[61],"amount":[62],"works":[64],"exist":[65],"on":[66,83,102,137],"using":[69,115],"perfectly":[70],"labelled":[71],"datasets":[72,145],"but":[73],"none":[74],"these":[76],"explore":[77],"impact":[79,93],"annotation":[81,169],"accuracy.":[86,105],"In":[87],"this":[88],"paper,":[89],"we":[90],"investigate":[91],"imperfect":[95,113],"labels":[96,114,162],"(both":[97],"noisy":[98],"missing":[100],"labels)":[101],"We":[106],"propose":[107],"system":[109],"that":[110,147,155],"automatically":[111],"generate":[112],"(called":[120],"annotator)":[121],"are":[123],"then":[124],"train":[127],"new":[129],"(target":[133],"model).":[134],"Our":[135],"analysis":[136],"two":[138,143],"models":[141,167],"benchmark":[144],"shows":[146],"proposed":[149],"scheme":[150],"achieves":[151],"closer":[153],"trained":[159],"with":[160],"perfect":[161],"showing":[163],"robustness":[164],"errors.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
