{"id":"https://openalex.org/W4401357508","doi":"https://doi.org/10.1109/access.2024.3439602","title":"Ensemble CNN-ViT Using Feature-Level Fusion for Gait Recognition","display_name":"Ensemble CNN-ViT Using Feature-Level Fusion for Gait Recognition","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401357508","doi":"https://doi.org/10.1109/access.2024.3439602"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3439602","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439602","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.2024.3439602","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018704343","display_name":"Jashila Nair Mogan","orcid":"https://orcid.org/0000-0002-7873-0033"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Jashila Nair Mogan","raw_affiliation_strings":["Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-7873-0033","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086127398","display_name":"Chin Poo Lee","orcid":"https://orcid.org/0000-0003-3679-8977"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Chin Poo Lee","raw_affiliation_strings":["Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-3679-8977","affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017532046","display_name":"Kian Ming Lim","orcid":"https://orcid.org/0000-0003-1929-7978"},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kian Ming Lim","raw_affiliation_strings":["School of Computer Science, University of Nottingham Ningbo China, Yinzhou, Ningbo, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0003-1929-7978","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Ningbo China, Yinzhou, Ningbo, Zhejiang, China","institution_ids":["https://openalex.org/I13591777"]}]}],"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":0.9727,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.72495766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"108573","last_page":"108583"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9936000108718872,"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"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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":0.7373332977294922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6518937349319458},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.6465410590171814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6210391521453857},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5290963649749756},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"Gait analysis","score":0.4556354582309723},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44161468744277954},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35308724641799927},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.24267521500587463},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07354986667633057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7373332977294922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6518937349319458},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6465410590171814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6210391521453857},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5290963649749756},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.4556354582309723},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44161468744277954},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35308724641799927},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.24267521500587463},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07354986667633057},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2024.3439602","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439602","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:shdl.mmu.edu.my:12922","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196753","display_name":"Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I173029219","host_organization_name":"Multimedia University","host_organization_lineage":["https://openalex.org/I173029219"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"NonPeerReviewed"},{"id":"pmh:oai:doaj.org/article:9969fcb20ab740fb92063157b7e7f124","is_oa":true,"landing_page_url":"https://doaj.org/article/9969fcb20ab740fb92063157b7e7f124","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 12, Pp 108573-108583 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3439602","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3439602","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":[{"id":"https://openalex.org/G4309384276","display_name":null,"funder_award_id":"FRGS/1/2021/ICT02/MMU/02/4","funder_id":"https://openalex.org/F4320321147","funder_display_name":"Ministry of Higher Education"}],"funders":[{"id":"https://openalex.org/F4320321147","display_name":"Ministry of Higher Education","ror":"https://ror.org/0512bh102"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1891905176","https://openalex.org/W1971358173","https://openalex.org/W1989696410","https://openalex.org/W2018331988","https://openalex.org/W2025085710","https://openalex.org/W2040270931","https://openalex.org/W2071576700","https://openalex.org/W2097117768","https://openalex.org/W2104335344","https://openalex.org/W2531409750","https://openalex.org/W2587763979","https://openalex.org/W2766064249","https://openalex.org/W2775676195","https://openalex.org/W2790787622","https://openalex.org/W2793243914","https://openalex.org/W2919322259","https://openalex.org/W2925351424","https://openalex.org/W2946327825","https://openalex.org/W2963446712","https://openalex.org/W2996910432","https://openalex.org/W3021014763","https://openalex.org/W3035040255","https://openalex.org/W3036199157","https://openalex.org/W3086951262","https://openalex.org/W3091988595","https://openalex.org/W3128064349","https://openalex.org/W3129376202","https://openalex.org/W3158746385","https://openalex.org/W3162464492","https://openalex.org/W3193780740","https://openalex.org/W3194247657","https://openalex.org/W4238732474","https://openalex.org/W4289110633","https://openalex.org/W4289830008","https://openalex.org/W4298005495","https://openalex.org/W4367598365","https://openalex.org/W4375946979","https://openalex.org/W4380898635","https://openalex.org/W6637373629","https://openalex.org/W6674914833","https://openalex.org/W6684191040","https://openalex.org/W6760532238","https://openalex.org/W6795171343","https://openalex.org/W7019254944"],"related_works":["https://openalex.org/W2133973503","https://openalex.org/W2471060339","https://openalex.org/W2148547327","https://openalex.org/W4226236273","https://openalex.org/W2125892956","https://openalex.org/W2790560349","https://openalex.org/W2130975749","https://openalex.org/W2493973380","https://openalex.org/W2394835211","https://openalex.org/W2809084995"],"abstract_inverted_index":{"Individual":[0],"deep":[1],"learning":[2],"models":[3,69,110],"showcase":[4],"impressive":[5],"performance;":[6],"however,":[7],"the":[8,19,27,39,51,59,98,104,127,130,138,165,212,216],"capacity":[9],"of":[10,22,41,49,61,94,164,199,215],"a":[11,34,76,121,150],"single":[12,35],"model":[13,36,117,144,219],"might":[14],"fall":[15],"short":[16],"in":[17,26],"capturing":[18],"full":[20],"spectrum":[21],"intricate":[23],"patterns":[24],"present":[25],"input":[28,102],"data.":[29],"Thus,":[30],"relying":[31],"solely":[32],"on":[33,170,201,205,209],"may":[37],"hamper":[38],"attainment":[40],"optimal":[42],"results":[43,181],"and":[44,67,108,133,147,177,207],"broader":[45],"generalization.":[46],"In":[47],"light":[48],"this,":[50],"paper":[52],"presents":[53],"an":[54],"ensemble":[55],"method":[56,167,195],"that":[57],"leverages":[58],"strengths":[60],"multiple":[62],"Convolutional":[63,105],"Neural":[64,106],"Networks":[65,107],"(CNNs)":[66],"Transformer":[68,109],"to":[70,103,111,125,186,224],"elevate":[71],"gait":[72,78,91,95,114,140],"recognition":[73],"performance.":[74],"Additionally,":[75],"novel":[77],"representation":[79,153],"named":[80],"windowed":[81,99],"Gait":[82],"Energy":[83],"Image":[84],"(GEI)":[85],"is":[86,101,118],"introduced,":[87],"obtained":[88],"by":[89,120],"averaging":[90],"frames":[92],"irrespective":[93],"cycles.":[96],"Firstly,":[97],"GEI":[100],"learn":[112],"significant":[113],"features.":[115],"Each":[116],"followed":[119],"Multilayer":[122],"Perceptron":[123],"(MLP)":[124],"encode":[126],"relationship":[128],"between":[129],"extracted":[131,139],"features":[132,141],"corresponding":[134],"class":[135],"labels.":[136],"Subsequently,":[137],"from":[142],"each":[143],"are":[145],"flattened":[146],"concatenated":[148],"into":[149],"cohesive":[151],"feature":[152],"before":[154],"passing":[155],"through":[156],"another":[157],"MLP":[158],"for":[159],"subject":[160],"classification.":[161],"The":[162,193],"performance":[163,214],"proposed":[166,194],"was":[168],"assessed":[169],"three":[171,191],"datasets:":[172],"OU-ISIR":[173,202],"dataset":[174],"D,":[175,203],"CASIA-B,":[176,206],"OU-LP":[178],"dataset.":[179],"Experimental":[180],"demonstrated":[182],"remarkable":[183],"improvements":[184],"compared":[185,223],"existing":[187],"methods":[188],"across":[189],"all":[190],"datasets.":[192],"achieved":[196],"accuracy":[197],"rates":[198],"100%":[200],"99.93%":[204],"99.94%":[208],"OU-LP,":[210],"showcasing":[211],"superior":[213],"Ensemble":[217],"CNN-ViT":[218],"using":[220],"feature-level":[221],"fusion":[222],"state-of-the-art":[225],"methods.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4}],"updated_date":"2026-06-13T07:54:00.901334","created_date":"2025-10-10T00:00:00"}
