{"id":"https://openalex.org/W4297910996","doi":"https://doi.org/10.1108/ijicc-05-2022-0161","title":"Research on pedestrian detection based on multi-level fine-grained YOLOX algorithm","display_name":"Research on pedestrian detection based on multi-level fine-grained YOLOX algorithm","publication_year":2022,"publication_date":"2022-09-24","ids":{"openalex":"https://openalex.org/W4297910996","doi":"https://doi.org/10.1108/ijicc-05-2022-0161"},"language":"en","primary_location":{"id":"doi:10.1108/ijicc-05-2022-0161","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-05-2022-0161","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","raw_type":"journal-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/A5100370868","display_name":"Hong Wang","orcid":"https://orcid.org/0000-0001-6872-8020"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Wang","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101927249","display_name":"Yong Xie","orcid":"https://orcid.org/0009-0003-1575-4104"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xie","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052754971","display_name":"Shasha Tian","orcid":"https://orcid.org/0000-0001-5837-330X"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shasha Tian","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414937","display_name":"Lu Zheng","orcid":"https://orcid.org/0000-0001-5079-4169"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Zheng","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012312447","display_name":"Xiaojie Dong","orcid":"https://orcid.org/0009-0004-7955-5603"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Dong","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100434313","display_name":"Yu Zhu","orcid":"https://orcid.org/0000-0002-5430-7847"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhu","raw_affiliation_strings":["Department of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100370868"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":0.6113,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67728689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"16","issue":"2","first_page":"295","last_page":"313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9976999759674072,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976999759674072,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.989300012588501,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9728999733924866,"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":0.8256366848945618},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.7402909994125366},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7269426584243774},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.550365686416626},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5230406522750854},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5184654593467712},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5122806429862976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47950583696365356},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.43019339442253113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41050493717193604},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34158486127853394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256366848945618},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.7402909994125366},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7269426584243774},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.550365686416626},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5230406522750854},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5184654593467712},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5122806429862976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47950583696365356},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.43019339442253113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41050493717193604},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34158486127853394},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijicc-05-2022-0161","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-05-2022-0161","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2752263152","https://openalex.org/W2769924742","https://openalex.org/W2793693263","https://openalex.org/W2883363148","https://openalex.org/W2884585870","https://openalex.org/W2894820835","https://openalex.org/W2895451584","https://openalex.org/W2896540732","https://openalex.org/W2925359305","https://openalex.org/W2928165649","https://openalex.org/W2990268359","https://openalex.org/W2991833700","https://openalex.org/W2996105331","https://openalex.org/W2998471151","https://openalex.org/W3012791016","https://openalex.org/W3013085568","https://openalex.org/W3018757597","https://openalex.org/W3032984651","https://openalex.org/W3034955056","https://openalex.org/W3035006004","https://openalex.org/W3045896538","https://openalex.org/W3082726303","https://openalex.org/W3094918646","https://openalex.org/W3095215020","https://openalex.org/W3099389178","https://openalex.org/W3104401316","https://openalex.org/W3111272232","https://openalex.org/W3111635878","https://openalex.org/W3133954504","https://openalex.org/W3138958001","https://openalex.org/W3152053255","https://openalex.org/W3152778632","https://openalex.org/W3157884962","https://openalex.org/W3183430956","https://openalex.org/W3215233137","https://openalex.org/W4366481765"],"related_works":["https://openalex.org/W4288602136","https://openalex.org/W2992551472","https://openalex.org/W2913413428","https://openalex.org/W4280575981","https://openalex.org/W2802018156","https://openalex.org/W2565999991","https://openalex.org/W2890135016","https://openalex.org/W2940690500","https://openalex.org/W4312696271","https://openalex.org/W2049141944"],"abstract_inverted_index":{"Purpose":[0],"The":[1,153,189,209],"purpose":[2],"of":[3,11,17,51,84,88,105,137,166,201],"the":[4,9,26,49,52,63,72,77,82,85,89,94,103,106,119,125,134,140,144,148,160,164,167,173,184,199],"study":[5,36,70],"is":[6,115],"to":[7,47,80,117,124],"address":[8,48],"problems":[10],"low":[12],"accuracy":[13],"and":[14,20,92,132,178,204,217],"missed":[15],"detection":[16,30,43,194,200],"occluded":[18,202],"pedestrians":[19,23,203],"small":[21,205],"target":[22,206],"when":[24,128],"using":[25],"YOLOX":[27,41,54,162,192],"general":[28],"object":[29],"algorithm":[31,55,169,195],"for":[32,62,102,147],"pedestrian":[33,42,95,130,185,193],"detection.":[34],"This":[35],"proposes":[37],"a":[38,58,108,212,218],"multi-level":[39,190,213],"fine-grained":[40,191,214],"algorithm.":[44],"Design/methodology/approach":[45],"First,":[46],"problem":[50],"original":[53,161],"in":[56],"obtaining":[57],"single":[59],"perceptual":[60,86],"field":[61,87],"feature":[64,67,90],"map":[65,91],"before":[66],"fusion,":[68],"this":[69],"improves":[71],"PAFPN":[73],"structure":[74],"by":[75,171,176,181],"adding":[76],"ResCoT":[78,215],"module":[79,113,216],"increase":[81],"diversity":[83],"divides":[93],"multi-scale":[96],"features":[97,131,136],"into":[98],"finer":[99],"granularity.":[100],"Second,":[101],"CSPLayer":[104],"PAFPN,":[107],"weight":[109,219],"gain-based":[110,220],"normalization-based":[111],"attention":[112,123,222],"(NAM)":[114],"proposed":[116],"make":[118],"model":[120],"pay":[121],"more":[122],"context":[126],"information":[127],"extracting":[129],"highlight":[133],"salient":[135],"pedestrians.":[138,207],"Finally,":[139],"authors":[141,210],"experimentally":[142],"determined":[143],"optimal":[145],"values":[146],"confidence":[149],"loss":[150],"function.":[151],"Findings":[152],"experimental":[154],"results":[155],"show":[156],"that,":[157],"compared":[158],"with":[159],"algorithm,":[163],"AP":[165],"improved":[168],"increased":[170,175,180],"2.90%,":[172],"Recall":[174],"3.57%,":[177],"F1":[179],"2%":[182],"on":[183],"dataset.":[186],"Research":[187],"limitations/implications":[188],"can":[196],"effectively":[197],"improve":[198],"Originality/value":[208],"introduce":[211],"NAM":[221],"module.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
