{"id":"https://openalex.org/W4360993699","doi":"https://doi.org/10.1109/tim.2023.3261909","title":"Label Enhancement-Based Multiscale Transformer for Palm-Vein Recognition","display_name":"Label Enhancement-Based Multiscale Transformer for Palm-Vein Recognition","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4360993699","doi":"https://doi.org/10.1109/tim.2023.3261909"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3261909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3261909","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5054571269","display_name":"Huafeng Qin","orcid":"https://orcid.org/0000-0003-4911-0393"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huafeng Qin","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-4911-0393","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Changqing Gong","orcid":"https://orcid.org/0000-0001-9017-1118"},"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":"Changqing Gong","raw_affiliation_strings":["School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-9017-1118","affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754583","display_name":"Yantao Li","orcid":"https://orcid.org/0000-0001-7648-5671"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yantao Li","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China","Chongqing University [Chongqing] (131 Yubei Rd, Shapingba, Chongqing - China)"],"raw_orcid":"https://orcid.org/0000-0001-7648-5671","affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]},{"raw_affiliation_string":"Chongqing University [Chongqing] (131 Yubei Rd, Shapingba, Chongqing - China)","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0002-7985-0037"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7985-0037","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038934826","display_name":"Moun\u00eem A. El\u2010Yacoubi","orcid":"https://orcid.org/0000-0002-7383-0588"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4387153010","display_name":"T\u00e9l\u00e9com SudParis","ror":"https://ror.org/05xvk4r52","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4387153010"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mounim A. El-Yacoubi","raw_affiliation_strings":["SAMOVAR, T&#x00E9;l&#x00E9;com SudParis, Centre National de la Recherche Scientifique (CNRS), Institut Polytechnique de Paris, Palaiseau, France","ARMEDIA-SAMOVAR - ARMEDIA (TELECOM Sudparis\r\n 9 rue Charles Fourier\r\n 91011 EVRY - France)"],"raw_orcid":"https://orcid.org/0000-0002-7383-0588","affiliations":[{"raw_affiliation_string":"SAMOVAR, T&#x00E9;l&#x00E9;com SudParis, Centre National de la Recherche Scientifique (CNRS), Institut Polytechnique de Paris, Palaiseau, France","institution_ids":["https://openalex.org/I1294671590"]},{"raw_affiliation_string":"ARMEDIA-SAMOVAR - ARMEDIA (TELECOM Sudparis\r\n 9 rue Charles Fourier\r\n 91011 EVRY - France)","institution_ids":["https://openalex.org/I4387153010"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0699,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92560256,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9995999932289124,"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":0.9995999932289124,"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/T14333","display_name":"Dermatoglyphics and Human Traits","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9337999820709229,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7213276028633118},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.674909770488739},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6677894592285156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6566748023033142},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5238794684410095},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5092962980270386},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.48696622252464294},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47669169306755066},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47094404697418213},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4143620729446411},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1280907690525055}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7213276028633118},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.674909770488739},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6677894592285156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6566748023033142},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5238794684410095},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5092962980270386},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.48696622252464294},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47669169306755066},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47094404697418213},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4143620729446411},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1280907690525055},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2023.3261909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3261909","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-04058053v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04058053","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement, 2023, 72, pp.1-1. &#x27E8;10.1109/TIM.2023.3261909&#x27E9;","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1148545545","display_name":null,"funder_award_id":"KJQN201900848","funder_id":"https://openalex.org/F4320324805","funder_display_name":"Chongqing Municipal Education Commission"},{"id":"https://openalex.org/G1546930127","display_name":null,"funder_award_id":"U20A20176","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"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/G3189868419","display_name":null,"funder_award_id":"CXQT21034","funder_id":"https://openalex.org/F4320321135","funder_display_name":"Chongqing University"},{"id":"https://openalex.org/G3456908973","display_name":null,"funder_award_id":"59676651E","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6458999915","display_name":"\u57fa\u4e8e\u884c\u4e3a\u7279\u5f81\u7684\u79fb\u52a8\u7528\u6237\u6301\u7eed\u8ba4\u8bc1\u65b9\u6cd5\u548c\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"62072061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321135","display_name":"Chongqing University","ror":"https://ror.org/023rhb549"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"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":101,"referenced_works":["https://openalex.org/W1512403036","https://openalex.org/W1686810756","https://openalex.org/W1963920031","https://openalex.org/W1965555277","https://openalex.org/W1969198379","https://openalex.org/W1974821667","https://openalex.org/W1991620112","https://openalex.org/W1997175872","https://openalex.org/W2014470493","https://openalex.org/W2032476112","https://openalex.org/W2033240662","https://openalex.org/W2038924852","https://openalex.org/W2066454034","https://openalex.org/W2079366010","https://openalex.org/W2096540110","https://openalex.org/W2097117768","https://openalex.org/W2098693229","https://openalex.org/W2102780391","https://openalex.org/W2118323481","https://openalex.org/W2119416456","https://openalex.org/W2122790104","https://openalex.org/W2136975665","https://openalex.org/W2138460174","https://openalex.org/W2140959843","https://openalex.org/W2144025519","https://openalex.org/W2194775991","https://openalex.org/W2328254514","https://openalex.org/W2330485005","https://openalex.org/W2552954853","https://openalex.org/W2599632008","https://openalex.org/W2604853352","https://openalex.org/W2619311872","https://openalex.org/W2624181600","https://openalex.org/W2740909158","https://openalex.org/W2766534271","https://openalex.org/W2785451509","https://openalex.org/W2791437400","https://openalex.org/W2793410607","https://openalex.org/W2811014381","https://openalex.org/W2884114979","https://openalex.org/W2884691787","https://openalex.org/W2917172368","https://openalex.org/W2919938126","https://openalex.org/W2929084559","https://openalex.org/W2932399282","https://openalex.org/W2942413398","https://openalex.org/W2945197573","https://openalex.org/W2952526090","https://openalex.org/W2956862036","https://openalex.org/W2958587321","https://openalex.org/W2962803115","https://openalex.org/W2963052338","https://openalex.org/W2963163009","https://openalex.org/W2963263347","https://openalex.org/W2963342610","https://openalex.org/W2964350391","https://openalex.org/W2981059842","https://openalex.org/W2982083293","https://openalex.org/W2983276939","https://openalex.org/W3003656584","https://openalex.org/W3005370840","https://openalex.org/W3034256998","https://openalex.org/W3093484105","https://openalex.org/W3111099392","https://openalex.org/W3118608800","https://openalex.org/W3131500599","https://openalex.org/W3132400026","https://openalex.org/W3132455321","https://openalex.org/W3134449933","https://openalex.org/W3138516171","https://openalex.org/W3151130473","https://openalex.org/W3166942762","https://openalex.org/W3175010480","https://openalex.org/W3176153963","https://openalex.org/W3197795290","https://openalex.org/W3200023241","https://openalex.org/W3206974845","https://openalex.org/W3214744507","https://openalex.org/W4200502778","https://openalex.org/W4205437765","https://openalex.org/W4205677231","https://openalex.org/W4205772041","https://openalex.org/W4212857616","https://openalex.org/W4214493665","https://openalex.org/W4214614183","https://openalex.org/W4214633470","https://openalex.org/W4226224676","https://openalex.org/W4285175773","https://openalex.org/W4287062814","https://openalex.org/W4290927683","https://openalex.org/W4293084194","https://openalex.org/W4311925372","https://openalex.org/W4385245566","https://openalex.org/W6637373629","https://openalex.org/W6713507025","https://openalex.org/W6726497184","https://openalex.org/W6749810415","https://openalex.org/W6796526935","https://openalex.org/W6797235774","https://openalex.org/W6798016242","https://openalex.org/W6841287799"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W2095239294","https://openalex.org/W3147744369","https://openalex.org/W2062586268","https://openalex.org/W2019582947","https://openalex.org/W3212688212","https://openalex.org/W4300873085","https://openalex.org/W4300552992"],"abstract_inverted_index":{"Vein":[0,82],"biometrics":[1],"is":[2,54,188,217],"a":[3,35,77,93,107,116,137,158,199],"high":[4],"security":[5],"and":[6,33,101,115,177,190,242,250,264,272],"privacy":[7],"preserving":[8],"identification":[9,262],"technology":[10],"that":[11,110,119,255],"has":[12],"received":[13],"increasing":[14],"attentions.":[15],"Although":[16],"deep":[17,283],"neural":[18,24],"networks":[19],"(DNNs),":[20],"such":[21],"as":[22],"convolutional":[23,108,139],"network":[25,140],"(CNN),":[26],"have":[27],"been":[28],"investigated":[29],"for":[30,62,84,152,168],"vein":[31,95,153,261],"recognition":[32,86],"achieved":[34],"significant":[36],"improvement":[37],"in":[38,48,87,219,237],"accuracy,":[39],"they":[40],"still":[41],"fail":[42],"to":[43,98,129,146,161,197,211,213,223],"model":[44],"long-range":[45],"pixel":[46],"dependencies":[47,122],"an":[49,163,174,220],"image.":[50,206],"Moreover,":[51],"their":[52],"performance":[53,241,268,278],"limited":[55],"because":[56],"the":[57,66,112,131,148,170,194,204,226,251,256,266,277],"one-hot":[58,195],"label":[59,142,150,165,185,196,201],"vector":[60,187],"employed":[61],"training":[63,179],"may":[64],"ignore":[65],"relevance":[67,132],"among":[68,123,133,269,281],"labels.":[69],"To":[70],"address":[71],"these":[72],"problems,":[73],"we":[74,91,135,208],"propose":[75,92],"LE-MSVT,":[76,215],"Label":[78],"Enhancement":[79],"based":[80,141,285],"Multi-Scale":[81],"Transformer":[83],"palm-vein":[85,248],"this":[88],"paper.":[89],"First,":[90],"multi-scale":[94,102],"transformer":[96],"(MSVT)":[97],"learn":[99,162],"robust":[100],"features,":[103],"which":[104,216],"consists":[105],"of":[106,203,230,239,279],"block":[109,118],"captures":[111],"local":[113],"information":[114,172],"self-attention":[117],"extracts":[120],"scale":[121],"images":[124,180],"with":[125,193],"different":[126,182],"scales.":[127],"Second,":[128],"capture":[130],"labels,":[134],"explore":[136],"graph":[138],"enhancement":[143],"(GCNLE)":[144],"approach":[145],"recover":[147],"realistic":[149,200],"distribution":[151,186,202],"classification":[154],"improvement.":[155],"GCNLE":[156,210,273],"exploits":[157],"multi-layer":[159],"perception":[160],"effective":[164],"correlation":[166],"matrix":[167],"extracting":[169],"relation":[171],"between":[173],"input":[175,205],"image":[176],"multiple":[178],"from":[181],"classes.":[183],"The":[184],"generated":[189],"then":[191],"combined":[192],"compute":[198],"Finally,":[207],"apply":[209],"MSVT":[212,231,240,258,280],"obtain":[214],"trained":[218],"end-to-end":[221],"way":[222],"further":[224],"improve":[225,276],"feature":[227],"representation":[228],"capacity":[229],"classifier.":[232],"We":[233],"conduct":[234],"extensive":[235],"experiments":[236],"terms":[238],"LE-MSVT":[243],"improvements":[244],"on":[245],"three":[246],"public":[247],"databases,":[249],"experimental":[252],"results":[253],"show":[254],"resulting":[257],"outperforms":[259],"other":[260,282],"approaches":[263],"achieves":[265],"best":[267],"existing":[270],"approaches,":[271],"can":[274],"greatly":[275],"learning":[284],"classifiers.":[286]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}
