{"id":"https://openalex.org/W4393041777","doi":"https://doi.org/10.1080/08839514.2024.2329859","title":"Label Noise Robust Crowd Counting with Loss Filtering Factor","display_name":"Label Noise Robust Crowd Counting with Loss Filtering Factor","publication_year":2024,"publication_date":"2024-03-21","ids":{"openalex":"https://openalex.org/W4393041777","doi":"https://doi.org/10.1080/08839514.2024.2329859"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2024.2329859","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2329859","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2329859?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2329859?download=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100577823","display_name":"Zhengmeng Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I898250095","display_name":"Industrial and Commercial Bank of China","ror":"https://ror.org/02zcab046","country_code":"CN","type":"other","lineage":["https://openalex.org/I898250095"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengmeng Xu","raw_affiliation_strings":["Postdoctoral Research Center, Industrial and Commercial Bank of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Postdoctoral Research Center, Industrial and Commercial Bank of China, Beijing, China","institution_ids":["https://openalex.org/I898250095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023704427","display_name":"Hai Lin","orcid":"https://orcid.org/0000-0002-4713-0414"},"institutions":[{"id":"https://openalex.org/I74593823","display_name":"Hebei Finance University","ror":"https://ror.org/04a9xrr47","country_code":"CN","type":"education","lineage":["https://openalex.org/I74593823"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Lin","raw_affiliation_strings":["School of Big Data Science, Hebei Finance University, Baoding, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data Science, Hebei Finance University, Baoding, China","institution_ids":["https://openalex.org/I74593823"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100394297","display_name":"Yufeng Chen","orcid":"https://orcid.org/0000-0003-0437-6788"},"institutions":[{"id":"https://openalex.org/I123387679","display_name":"Uppsala University","ror":"https://ror.org/048a87296","country_code":"SE","type":"education","lineage":["https://openalex.org/I123387679"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yufeng Chen","raw_affiliation_strings":["Department of Information Technology, Uppsala University, Uppsala, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Uppsala University, Uppsala, Sweden","institution_ids":["https://openalex.org/I123387679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047237748","display_name":"Yanli Li","orcid":"https://orcid.org/0000-0001-9842-2209"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yanli Li","raw_affiliation_strings":["School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047237748"],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":0.8335,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75438631,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"38","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9966999888420105,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.8376940488815308},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6176648736000061},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.4774478077888489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38498327136039734},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0729227066040039}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8376940488815308},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6176648736000061},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.4774478077888489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38498327136039734},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0729227066040039},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/08839514.2024.2329859","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2329859","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2329859?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:DiVA.org:uu-530043","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-530043","pdf_url":null,"source":{"id":"https://openalex.org/S4306402042","display_name":"Uppsala University Publications (Uppsala University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I123387679","host_organization_name":"Uppsala University","host_organization_lineage":["https://openalex.org/I123387679"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:5164efe2c855445b86560e46d88f0b60","is_oa":true,"landing_page_url":"https://doaj.org/article/5164efe2c855445b86560e46d88f0b60","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 38, Iss 1 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2024.2329859","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2024.2329859","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2329859?download=true","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393041777.pdf","grobid_xml":"https://content.openalex.org/works/W4393041777.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W2072232009","https://openalex.org/W2120815373","https://openalex.org/W2123175289","https://openalex.org/W2161841955","https://openalex.org/W2257979135","https://openalex.org/W2463631526","https://openalex.org/W2517615595","https://openalex.org/W2520826941","https://openalex.org/W2566079294","https://openalex.org/W2600230189","https://openalex.org/W2784220689","https://openalex.org/W2798489385","https://openalex.org/W2803237185","https://openalex.org/W2811245964","https://openalex.org/W2883929025","https://openalex.org/W2885593519","https://openalex.org/W2886443245","https://openalex.org/W2895051362","https://openalex.org/W2938694836","https://openalex.org/W2943493972","https://openalex.org/W2963172723","https://openalex.org/W2963735582","https://openalex.org/W2963838390","https://openalex.org/W2964081807","https://openalex.org/W2964209782","https://openalex.org/W2964285767","https://openalex.org/W2969620138","https://openalex.org/W2972451902","https://openalex.org/W2991203386","https://openalex.org/W2996335500","https://openalex.org/W2996703886","https://openalex.org/W3000998348","https://openalex.org/W3004672782","https://openalex.org/W3013987429","https://openalex.org/W3015395800","https://openalex.org/W3035702670","https://openalex.org/W3045455261","https://openalex.org/W3087861058","https://openalex.org/W3097060387","https://openalex.org/W3127995199","https://openalex.org/W3132588545","https://openalex.org/W3174519905","https://openalex.org/W3176458063","https://openalex.org/W3177211876","https://openalex.org/W4207050521","https://openalex.org/W4220956840","https://openalex.org/W4281743493","https://openalex.org/W4282939170","https://openalex.org/W4285129393","https://openalex.org/W4292859076","https://openalex.org/W4296739197","https://openalex.org/W4307008675","https://openalex.org/W4309903996","https://openalex.org/W4313182800","https://openalex.org/W4313281881","https://openalex.org/W4317889718","https://openalex.org/W4321192600","https://openalex.org/W4322489886","https://openalex.org/W4323308899","https://openalex.org/W4323669573","https://openalex.org/W4366378414","https://openalex.org/W4377696102","https://openalex.org/W4385252090","https://openalex.org/W4388273523","https://openalex.org/W6783507135"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Crowd":[0,80],"counting,":[1],"a":[2,26,165],"crucial":[3],"computer":[4,172],"vision":[5],"task,":[6],"aims":[7],"at":[8,28],"estimating":[9],"the":[10,29,32,55,69,75,108,169,177],"number":[11],"of":[12,31,110,125,149,156,171,180],"individuals":[13],"in":[14,18,61,127,133,140,168,175,182],"various":[15],"environments.Each":[16],"person":[17],"crowd":[19,183],"counting":[20,184],"datasets":[21],"is":[22],"typically":[23],"annotated":[24],"by":[25,54,90],"point":[27],"center":[30],"head.However,":[33],"challenges":[34],"like":[35],"dense":[36],"crowds,":[37],"diverse":[38],"scenarios,":[39],"significant":[40,166],"obscuration,":[41],"and":[42,64,74,119,138],"low":[43],"resolution":[44],"lead":[45],"to":[46,57,97],"inevitable":[47],"label":[48,91],"noise,":[49],"adversely":[50],"impacting":[51],"model":[52,59,162],"performance.Driven":[53],"need":[56],"enhance":[58],"robustness":[60],"noisy":[62],"environments":[63],"improve":[65],"accuracy,":[66],"we":[67],"propose":[68],"Loss":[70],"Filtering":[71],"Factor":[72],"(LFF)":[73],"corresponding":[76],"Label":[77],"Noise":[78],"Robust":[79],"Counting":[81],"(LNRCC)":[82],"training":[83],"scheme.LFF":[84],"innovatively":[85],"filters":[86],"out":[87],"losses":[88],"caused":[89],"noise":[92],"during":[93],"training,":[94],"enabling":[95],"models":[96,118],"focus":[98],"on":[99],"accurate":[100],"data,":[101],"thereby":[102],"increasing":[103],"reliability.Our":[104],"extensive":[105],"experiments":[106],"demonstrate":[107],"effectiveness":[109],"LNRCC,":[111],"which":[112],"consistently":[113],"improves":[114],"performance":[115],"across":[116],"all":[117],"datasets,":[120],"with":[121,153],"an":[122],"average":[123],"enhancement":[124],"3.68%":[126],"Mean":[128,134,143],"Absolute":[129,144],"Error":[130,136,145],"(MAE),":[131],"6.7%":[132],"Squared":[135],"(MSE)":[137],"4.68%":[139],"Grid":[141],"Average":[142],"(GAME).The":[146],"universal":[147],"applicability":[148],"this":[150],"approach,":[151],"coupled":[152],"its":[154],"ease":[155],"integration":[157],"into":[158],"any":[159],"neural":[160],"network":[161],"architecture,":[163],"marks":[164],"advancement":[167],"field":[170],"vision,":[173],"particularly":[174],"addressing":[176],"pivotal":[178],"issue":[179],"accuracy":[181],"under":[185],"challenging":[186],"conditions.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-12T06:13:28.667946","created_date":"2025-10-10T00:00:00"}