{"id":"https://openalex.org/W4401163660","doi":"https://doi.org/10.1109/access.2024.3436007","title":"ABDviaMSIFAT: Abnormal Crowd Behavior Detection Utilizing a Multi-Source Information Fusion Technique","display_name":"ABDviaMSIFAT: Abnormal Crowd Behavior Detection Utilizing a Multi-Source Information Fusion Technique","publication_year":2024,"publication_date":"2024-07-31","ids":{"openalex":"https://openalex.org/W4401163660","doi":"https://doi.org/10.1109/access.2024.3436007"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3436007","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436007","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3436007","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087272333","display_name":"A.A. Hamid","orcid":"https://orcid.org/0009-0006-3682-9189"},"institutions":[{"id":"https://openalex.org/I39268498","display_name":"University of Isfahan","ror":"https://ror.org/05h9t7759","country_code":"IR","type":"education","lineage":["https://openalex.org/I39268498"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ali Ahmad Hamid","raw_affiliation_strings":["Computer Engineering Faculty, University of Isfahan, Isfahan, Iran"],"raw_orcid":"https://orcid.org/0009-0006-3682-9189","affiliations":[{"raw_affiliation_string":"Computer Engineering Faculty, University of Isfahan, Isfahan, Iran","institution_ids":["https://openalex.org/I39268498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057801852","display_name":"S. Amirhassan Monadjemi","orcid":"https://orcid.org/0000-0002-8094-2449"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"S. Amirhassan Monadjemi","raw_affiliation_strings":["School of Computing, National University of Singapore, Lower Kent Ridge, Singapore","School of Computing, National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Lower Kent Ridge, Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056244293","display_name":"Bijan Shoushtarian","orcid":"https://orcid.org/0000-0003-1993-6370"},"institutions":[{"id":"https://openalex.org/I39268498","display_name":"University of Isfahan","ror":"https://ror.org/05h9t7759","country_code":"IR","type":"education","lineage":["https://openalex.org/I39268498"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Bijan Shoushtarian","raw_affiliation_strings":["Computer Engineering Faculty, University of Isfahan, Isfahan, Iran","Department of computer Engineering Techniques, Nasiriyah, Iraq"],"raw_orcid":"https://orcid.org/0000-0003-1993-6370","affiliations":[{"raw_affiliation_string":"Computer Engineering Faculty, University of Isfahan, Isfahan, Iran","institution_ids":["https://openalex.org/I39268498"]},{"raw_affiliation_string":"Department of computer Engineering Techniques, Nasiriyah, Iraq","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2219,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82540611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"75000","last_page":"75019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9984999895095825,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9972000122070312,"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":0.8376213908195496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6564681529998779},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6096140146255493},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5792202949523926},{"id":"https://openalex.org/keywords/crowds","display_name":"Crowds","score":0.5378687977790833},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5153924226760864},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.49458858370780945},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4915235936641693},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.46031495928764343},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4475645124912262},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4471903443336487},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.4358386695384979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43252986669540405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39076370000839233},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3835826814174652},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14353176951408386}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8376213908195496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6564681529998779},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6096140146255493},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5792202949523926},{"id":"https://openalex.org/C2777852691","wikidata":"https://www.wikidata.org/wiki/Q13430821","display_name":"Crowds","level":2,"score":0.5378687977790833},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5153924226760864},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.49458858370780945},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4915235936641693},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.46031495928764343},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4475645124912262},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4471903443336487},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.4358386695384979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43252986669540405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39076370000839233},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3835826814174652},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14353176951408386},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3436007","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436007","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:16345be172024981a9bdc8e3d8d32519","is_oa":true,"landing_page_url":"https://doaj.org/article/16345be172024981a9bdc8e3d8d32519","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":"IEEE Access, Vol 13, Pp 75000-75019 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3436007","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3436007","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W48616921","https://openalex.org/W1964846093","https://openalex.org/W2093986007","https://openalex.org/W2107323262","https://openalex.org/W2124211486","https://openalex.org/W2154889144","https://openalex.org/W2301943589","https://openalex.org/W2540481276","https://openalex.org/W2606538621","https://openalex.org/W2739846485","https://openalex.org/W2772616460","https://openalex.org/W2913163239","https://openalex.org/W2958103299","https://openalex.org/W2963111876","https://openalex.org/W2963240734","https://openalex.org/W2992018042","https://openalex.org/W2999718646","https://openalex.org/W3007303524","https://openalex.org/W3008186164","https://openalex.org/W3017055521","https://openalex.org/W3119156135","https://openalex.org/W3134666949","https://openalex.org/W3148708966","https://openalex.org/W3216417916","https://openalex.org/W4200335893","https://openalex.org/W4291825285","https://openalex.org/W4293047335","https://openalex.org/W4318328257","https://openalex.org/W4379983700","https://openalex.org/W4382467789","https://openalex.org/W4388145661","https://openalex.org/W4389482647","https://openalex.org/W4391512994","https://openalex.org/W4392910542","https://openalex.org/W6674330103","https://openalex.org/W6682175746","https://openalex.org/W6796223860","https://openalex.org/W6841210382","https://openalex.org/W6910727743"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W4380433113","https://openalex.org/W4386072068","https://openalex.org/W252339960","https://openalex.org/W2390529043","https://openalex.org/W2946096271","https://openalex.org/W2378320433","https://openalex.org/W2295423552","https://openalex.org/W2358343511"],"abstract_inverted_index":{"Detecting":[0],"abnormal":[1,214],"crowd":[2,18],"behavior":[3,45,80],"in":[4,46,62,131,158,222],"surveillance":[5],"videos":[6],"is":[7],"a":[8,26,63,95,122,197,209],"significant":[9],"challenge":[10],"due":[11],"to":[12,38,57,107,125,141,166],"the":[13,40,72,76,83,90,114,118,136,152,159,179],"intricate":[14],"and":[15,121,156,169,181,194,205,226],"constantly":[16],"evolving":[17],"dynamics.":[19],"To":[20],"solve":[21],"this":[22],"issue,":[23],"we":[24,93],"suggest":[25],"new":[27],"method":[28,140],"that":[29,54,102,189],"combines":[30,113],"data":[31],"from":[32,175],"various":[33],"sources":[34],"with":[35,117],"different":[36],"characteristics":[37],"enhance":[39],"precision":[41],"of":[42,75,85,154,173,183,213,224],"detecting":[43],"human":[44],"crowds.":[47],"Our":[48,200,216],"approach":[49,201,218],"involves":[50],"two":[51,176],"separate":[52],"pipelines":[53,177],"work":[55],"simultaneously":[56],"produce":[58],"scores":[59,67,168,174],"for":[60,71,79,129],"frames":[61],"video":[64,132],"segment.":[65],"These":[66],"are":[68],"later":[69],"modified":[70],"individual":[73],"level":[74],"group,":[77],"allowing":[78],"recognition":[81],"through":[82],"assessment":[84],"fuzzy":[86,187],"logic":[87],"functions.":[88],"In":[89],"first":[91],"pipeline,":[92],"utilize":[94],"depth-wise":[96],"Separable":[97],"Convolutional":[98],"Neural":[99],"Network":[100],"(DWS-CNN)":[101],"provides":[103],"reduced":[104],"filtering":[105],"compared":[106],"standard":[108],"CNNs.":[109],"The":[110],"second":[111],"pipeline":[112],"LiteFlowNet":[115],"detector":[116],"MOSSE":[119],"tracker":[120],"DSC-GRU":[123],"network":[124],"generate":[126],"high-level":[127],"captions":[128],"objects":[130],"frames.":[133],"We":[134],"implement":[135],"weighted":[137,148,171],"average":[138],"(WA)":[139],"improve":[142],"anomaly":[143],"detection":[144],"accuracy.":[145],"Methods":[146],"like":[147],"averages":[149,172],"can":[150],"mitigate":[151],"influence":[153],"outliers":[155],"noise":[157],"outcomes":[160],"or":[161],"evaluations.":[162],"Utilizing":[163],"linguistic":[164],"variables":[165],"represent":[167],"computing":[170],"enhances":[178],"quality":[180],"reliability":[182],"these":[184],"variables,":[185],"creating":[186],"predicates":[188],"characterize":[190],"people\u2019s":[191],"movements,":[192],"presence,":[193],"responses":[195],"at":[196],"microscopic":[198],"scale.":[199],"exceeds":[202],"conventional":[203],"visual":[204],"motion-centric":[206],"methods,":[207],"enabling":[208],"more":[210],"comprehensive":[211],"grasp":[212],"behaviors.":[215],"suggested":[217],"outperforms":[219],"state-of-the-art":[220],"methods":[221],"terms":[223],"effectiveness":[225],"performance":[227],"based":[228],"on":[229,232],"tests":[230],"done":[231],"well-known":[233],"datasets.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
