{"id":"https://openalex.org/W7148532588","doi":"https://doi.org/10.1109/tifs.2026.3679936","title":"Neural Architecture Search-Based Global\u2013Local Vision Mamba for Palm-Vein Recognition","display_name":"Neural Architecture Search-Based Global\u2013Local Vision Mamba for Palm-Vein Recognition","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7148532588","doi":"https://doi.org/10.1109/tifs.2026.3679936"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2026.3679936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3679936","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Forensics and Security","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/A5132806997","display_name":"Huafeng Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huafeng Qin","raw_affiliation_strings":["Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-4911-0393","affiliations":[{"raw_affiliation_string":"Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132800326","display_name":"Yuming Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Fu","raw_affiliation_strings":["Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-1937-4377","affiliations":[{"raw_affiliation_string":"Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jing Chen","orcid":"https://orcid.org/0009-0000-5614-0705"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Chen","raw_affiliation_strings":["Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-5614-0705","affiliations":[{"raw_affiliation_string":"Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132806115","display_name":"Mounim A. El-Yacoubi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145102","display_name":"Institut Polytechnique de Paris","ror":"https://ror.org/042tfbd02","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mounim A. El-Yacoubi","raw_affiliation_strings":["SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris, Palaiseau, France"],"raw_orcid":"https://orcid.org/0000-0002-7383-0588","affiliations":[{"raw_affiliation_string":"SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris, Palaiseau, France","institution_ids":["https://openalex.org/I4210145102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132827306","display_name":"Xinbo Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-7985-0037","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124001272","display_name":"Feng Xi","orcid":null},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xi","raw_affiliation_strings":["Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5132806997"],"corresponding_institution_ids":["https://openalex.org/I145581781"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70445261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"3766","last_page":"3780"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.8097000122070312,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10828","display_name":"Biometric Identification and Security","score":0.8097000122070312,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13192","display_name":"Forensic Fingerprint Detection Methods","score":0.020999999716877937,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10641","display_name":"Central Venous Catheters and Hemodialysis","score":0.01269999984651804,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6837999820709229},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6182000041007996},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5439000129699707},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5174999833106995},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4964999854564667},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4823000133037567},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46380001306533813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7781999707221985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7077999711036682},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6837999820709229},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6182000041007996},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5439000129699707},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5174999833106995},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4964999854564667},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4823000133037567},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46380001306533813},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4115999937057495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35589998960494995},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3089999854564667},{"id":"https://openalex.org/C15569618","wikidata":"https://www.wikidata.org/wiki/Q3561421","display_name":"Liveness","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.27480000257492065}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2026.3679936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2026.3679936","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6047794818878174}],"awards":[{"id":"https://openalex.org/G2394222010","display_name":null,"funder_award_id":"61976030","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2775522001","display_name":null,"funder_award_id":"62506054","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3420371645","display_name":null,"funder_award_id":"CSTB2024NSCQ-MSX1118","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G354082066","display_name":null,"funder_award_id":"KJZD-M202500804","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G6458999915","display_name":null,"funder_award_id":"62072061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324805","display_name":"Chongqing Municipal Education Commission","ror":"https://ror.org/031nm5713"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Owing":[0],"to":[1,92,113,122,131,162,209],"its":[2],"inherent":[3],"attributes":[4],"of":[5,127,141,189,248],"high":[6],"security,":[7],"privacy":[8],"preservation,":[9],"and":[10,75,97,153,195,223,272],"liveness":[11],"detection,":[12],"vein":[13,104,207,239,270,274],"recognition":[14],"has":[15,43],"garnered":[16],"significant":[17],"attention,":[18],"with":[19,39,159,167],"deep":[20],"learning":[21,249],"(DL)":[22],"models":[23],"prevailing":[24],"in":[25],"the":[26,115,124,186,215,224,258],"field.":[27],"In":[28,256],"particular,":[29],"Mamba,":[30],"a":[31,83,110,137,174],"recent":[32],"DL":[33],"architecture":[34,66,188,271],"showing":[35],"robust":[36],"feature":[37,55,60,105,125],"representation":[38,126],"linear":[40],"computational":[41],"complexity,":[42],"been":[44],"applied":[45],"successfully":[46],"for":[47,102,185,276],"visual":[48,259],"tasks.":[49],"However,":[50],"Vision":[51,89,128],"Mamba":[52,65,90,112,145,168],"captures":[53],"long-distance":[54],"dependencies":[56,99,116],"but":[57],"deteriorates":[58],"local":[59,95,165,273],"details.":[61],"Besides,":[62],"manually":[63],"designing":[64],"based":[67],"on":[68,204,236],"human":[69],"prior":[70],"knowledge":[71],"is":[72,246],"very":[73],"time-consuming":[74],"error-prone.":[76],"To":[77],"address":[78],"these":[79],"limitations,":[80],"we":[81,108,135,172],"propose":[82,136,173],"hybrid":[84],"network":[85],"structure":[86],"named":[87],"Global-local":[88,175],"(GLVM)":[91],"learn":[93,114,132],"both":[94],"correlations":[96],"global":[98,169,269],"within":[100],"images":[101],"comprehensive":[103],"representation.":[106],"Second,":[107],"design":[109],"Multi-head":[111,144],"along":[117],"different":[118],"directions,":[119],"so":[120],"as":[121],"improve":[123],"Mamba.":[129],"Third,":[130],"complementary":[133],"features,":[134],"ConvMamba":[138],"block":[139],"consisting":[140],"three":[142],"branches:":[143],"branch":[146,151],"(MHMamba),":[147],"Feature":[148],"Iteration":[149],"Unit":[150],"(FIU),":[152],"Convolutional":[154],"Neural":[155,177],"Network":[156],"(CNN)":[157],"branch,":[158],"FIU":[160],"aiming":[161],"fuse":[163],"convolutional":[164],"features":[166,252],"representations.":[170],"Finally,":[171],"Alternate":[176],"Architecture":[178],"Search":[179],"(GLNAS)":[180],"method,":[181],"which":[182,241],"alternately":[183],"searches":[184],"optimal":[187],"GLVM":[190],"through":[191],"weight":[192],"entanglement":[193],"strategy":[194],"evolutionary":[196],"algorithm.":[197],"We":[198],"have":[199],"carried":[200],"out":[201],"rigorous":[202],"experiments":[203,261],"five":[205,237],"public":[206,238],"datasets":[208],"assess":[210],"performance.":[211],"Our":[212],"approach":[213,245,266],"achieves":[214],"highest":[216],"96.84%,":[217],"99.63%,":[218],"95.73%,":[219],"99.72%,":[220],"99.14%":[221],"accuracies":[222],"lowest":[225],"0.27%,":[226],"0.07%,":[227,229],"0.48%,":[228],"0.12%":[230],"EER":[231],"among":[232],"all":[233],"existing":[234,254],"approaches":[235],"datasets,":[240],"demonstrates":[242],"that":[243,264],"our":[244,265],"capable":[247],"more":[250,268],"complete":[251],"than":[253],"approaches.":[255],"addition,":[257],"assessment":[260],"also":[262],"show":[263],"extracts":[267],"detail":[275],"recognition.":[277]},"counts_by_year":[],"updated_date":"2026-04-11T06:13:24.991567","created_date":"2026-04-03T00:00:00"}