{"id":"https://openalex.org/W3014462183","doi":"https://doi.org/10.1109/access.2020.2984711","title":"Finger Vein Verification Algorithm Based on Fully Convolutional Neural Network and Conditional Random Field","display_name":"Finger Vein Verification Algorithm Based on Fully Convolutional Neural Network and Conditional Random Field","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3014462183","doi":"https://doi.org/10.1109/access.2020.2984711","mag":"3014462183"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2984711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09052656.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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://ieeexplore.ieee.org/ielx7/6287639/8948470/09052656.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077839839","display_name":"Junying Zeng","orcid":"https://orcid.org/0000-0002-7559-0637"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junying Zeng","raw_affiliation_strings":["Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0002-7559-0637","affiliations":[{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380509","display_name":"Fan Wang","orcid":"https://orcid.org/0000-0002-2261-4789"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Wang","raw_affiliation_strings":["Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0002-2261-4789","affiliations":[{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086877568","display_name":"Jianxiang Deng","orcid":"https://orcid.org/0000-0002-7363-2274"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxiang Deng","raw_affiliation_strings":["Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0002-7363-2274","affiliations":[{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016322236","display_name":"Chuanbo Qin","orcid":"https://orcid.org/0000-0001-7189-5196"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanbo Qin","raw_affiliation_strings":["Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0001-7189-5196","affiliations":[{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017146820","display_name":"Yikui Zhai","orcid":"https://orcid.org/0000-0003-0154-9743"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN","IT"],"is_corresponding":false,"raw_author_name":"Yikui Zhai","raw_affiliation_strings":["Departimento di Information, Universita Degli Studi di Milano, Milano, Italy","Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0003-0154-9743","affiliations":[{"raw_affiliation_string":"Departimento di Information, Universita Degli Studi di Milano, Milano, Italy","institution_ids":["https://openalex.org/I189158943"]},{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081248268","display_name":"Junying Gan","orcid":"https://orcid.org/0000-0002-6418-7316"},"institutions":[{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junying Gan","raw_affiliation_strings":["Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"raw_orcid":"https://orcid.org/0000-0002-6418-7316","affiliations":[{"raw_affiliation_string":"Department of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009147954","display_name":"Vincenzo Piuri","orcid":"https://orcid.org/0000-0003-3178-8198"},"institutions":[{"id":"https://openalex.org/I189158943","display_name":"University of Milan","ror":"https://ror.org/00wjc7c48","country_code":"IT","type":"education","lineage":["https://openalex.org/I189158943"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vincenzo Piuri","raw_affiliation_strings":["Departimento di Information, Universita Degli Studi di Milano, Milano, Italy"],"raw_orcid":"https://orcid.org/0000-0003-3178-8198","affiliations":[{"raw_affiliation_string":"Departimento di Information, Universita Degli Studi di Milano, Milano, Italy","institution_ids":["https://openalex.org/I189158943"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5077839839"],"corresponding_institution_ids":["https://openalex.org/I4210151615"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.406,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95284436,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"65402","last_page":"65419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9990000128746033,"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":0.9990000128746033,"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/T10751","display_name":"Forensic and Genetic Research","score":0.9772999882698059,"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/T14333","display_name":"Dermatoglyphics and Human Traits","score":0.9746999740600586,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.8153670430183411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7655036449432373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6329601407051086},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6294870376586914},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5823825001716614},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5131862759590149},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5126549601554871},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5083445906639099},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4933399260044098},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47674521803855896},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4715554714202881},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14564451575279236}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.8153670430183411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7655036449432373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6329601407051086},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6294870376586914},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5823825001716614},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5131862759590149},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5126549601554871},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5083445906639099},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4933399260044098},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47674521803855896},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4715554714202881},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14564451575279236},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2020.2984711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09052656.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:air.unimi.it:2434/729904","is_oa":true,"landing_page_url":"http://hdl.handle.net/2434/729904","pdf_url":null,"source":{"id":"https://openalex.org/S4306400516","display_name":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I189158943","host_organization_name":"University of Milan","host_organization_lineage":["https://openalex.org/I189158943"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:4e4b2e6870bb4900bfc15e48091fdaa4","is_oa":true,"landing_page_url":"https://doaj.org/article/4e4b2e6870bb4900bfc15e48091fdaa4","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 8, Pp 65402-65419 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2984711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2984711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09052656.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/G1288007078","display_name":null,"funder_award_id":"2019A1515010716","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G1491241926","display_name":null,"funder_award_id":"2018KZDXM073","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5177878884","display_name":null,"funder_award_id":"2019KZDZX1017","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5917608087","display_name":null,"funder_award_id":"61771347","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/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3014462183.pdf","grobid_xml":"https://content.openalex.org/works/W3014462183.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W191940071","https://openalex.org/W1535130427","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1934184906","https://openalex.org/W1955055330","https://openalex.org/W1963920031","https://openalex.org/W1966602166","https://openalex.org/W1974821667","https://openalex.org/W1991620112","https://openalex.org/W1997175872","https://openalex.org/W2004617923","https://openalex.org/W2014470493","https://openalex.org/W2038924852","https://openalex.org/W2068999607","https://openalex.org/W2078740505","https://openalex.org/W2079981574","https://openalex.org/W2096540110","https://openalex.org/W2102780391","https://openalex.org/W2114214092","https://openalex.org/W2118323481","https://openalex.org/W2119416456","https://openalex.org/W2122647985","https://openalex.org/W2124592697","https://openalex.org/W2138460174","https://openalex.org/W2143612262","https://openalex.org/W2146156528","https://openalex.org/W2161236525","https://openalex.org/W2161315665","https://openalex.org/W2166524747","https://openalex.org/W2170942820","https://openalex.org/W2194775991","https://openalex.org/W2275037134","https://openalex.org/W2490846508","https://openalex.org/W2527341761","https://openalex.org/W2535516436","https://openalex.org/W2598954556","https://openalex.org/W2599632008","https://openalex.org/W2601564443","https://openalex.org/W2604853352","https://openalex.org/W2624181600","https://openalex.org/W2788906943","https://openalex.org/W2798122215","https://openalex.org/W2893920965","https://openalex.org/W2896194744","https://openalex.org/W2898910301","https://openalex.org/W2915035468","https://openalex.org/W2919938126","https://openalex.org/W2942413398","https://openalex.org/W2949117887","https://openalex.org/W2952793010","https://openalex.org/W2963180316","https://openalex.org/W2964227007","https://openalex.org/W2965176902","https://openalex.org/W2983303316","https://openalex.org/W4294226146","https://openalex.org/W6631907406","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6750469568","https://openalex.org/W6755808572","https://openalex.org/W6770094702"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W2964954556","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Owing":[0],"to":[1,20,32,40,58,73,90,123,200,234],"the":[2,13,46,65,82,95,101,105,111,119,129,140,146,151,155,163,174,184,188,198,202,208],"complexity":[3],"of":[4,67,183],"finger":[5,25,224],"vein":[6,26,42,225],"patterns":[7],"in":[8,104,206,216],"shape":[9],"and":[10,23,75,126,136,145,176,229],"spatial":[11],"dependence,":[12],"existing":[14],"methods":[15],"suffer":[16],"from":[17],"an":[18,37],"inability":[19],"obtain":[21],"accurate":[22],"stable":[24],"features.":[27],"This":[28],"paper,":[29],"so":[30,186],"as":[31,173,180],"compensate":[33],"this":[34,217],"defect,":[35],"proposes":[36],"end-to-end":[38],"model":[39,189],"extract":[41],"textures":[43],"through":[44,99],"integrating":[45],"fully":[47,156,191],"convolutional":[48,157],"neural":[49,142,158],"network":[50,143,148,159,211],"(FCN)":[51],"with":[52,77,87,165,194,231,244],"conditional":[53],"random":[54],"field":[55],"(CRF).":[56],"Firstly,":[57],"reduce":[59],"missing":[60],"pixels":[61],"during":[62],"ROI":[63],"extraction,":[64],"method":[66],"sliding":[68],"window":[69],"summation":[70],"is":[71,160,178],"employed":[72],"filter":[74],"adjusted":[76],"self-built":[78],"tools.":[79],"In":[80],"addition,":[81],"traditional":[83],"baselines":[84],"are":[85],"endowed":[86],"different":[88],"weights":[89],"automatically":[91],"assign":[92],"labels.":[93],"Secondly,":[94],"deformable":[96],"convolution":[97],"network,":[98],"replacing":[100],"plain":[102],"counterparts":[103],"standard":[106],"U-Net":[107],"mode,":[108],"can":[109,132,190],"capture":[110],"complex":[112],"venous":[113],"structural":[114],"features":[115,131],"by":[116,138],"adaptively":[117],"adjusting":[118],"receptive":[120],"fields":[121],"according":[122],"veins'":[124],"scales":[125],"shapes.":[127],"Moreover,":[128],"above":[130],"be":[133],"further":[134],"mined":[135],"accumulated":[137],"combining":[139],"recurrent":[141],"(RNN)":[144],"residual":[147],"(ResNet).":[149],"With":[150],"steps":[152],"mentioned":[153],"above,":[154],"constructed.":[161],"Finally,":[162],"CRF":[164,193],"Gaussian":[166],"pairwise":[167],"potential":[168],"conducts":[169],"mean-field":[170],"approximate":[171],"inference":[172],"RNN,":[175],"then":[177],"embedded":[179],"a":[181],"part":[182],"FCN,":[185],"that":[187],"integrate":[192],"FCNs,":[195],"which":[196],"provides":[197],"possibility":[199],"involve":[201],"usual":[203],"back-propagation":[204],"algorithm":[205],"training":[207],"whole":[209],"deep":[210],"end-to-end.":[212],"The":[213],"proposed":[214],"models":[215,247],"paper":[218],"were":[219],"tested":[220],"on":[221,239],"three":[222],"public":[223],"datasets":[226],"SDUMLA,":[227],"MMCBNU":[228],"HKPU":[230],"experimental":[232],"results":[233],"certify":[235],"their":[236],"superior":[237],"performance":[238],"finger-vein":[240],"verification":[241],"tasks":[242],"compared":[243],"other":[245],"equivalent":[246],"including":[248],"U-Net.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2020-04-10T00:00:00"}