{"id":"https://openalex.org/W4399563735","doi":"https://doi.org/10.1109/tifs.2024.3413631","title":"Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings","display_name":"Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399563735","doi":"https://doi.org/10.1109/tifs.2024.3413631"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2024.3413631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3413631","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/A5027893701","display_name":"Steven A. Grosz","orcid":"https://orcid.org/0000-0002-9186-3543"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Steven A. Grosz","raw_affiliation_strings":["Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-9186-3543","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013188362","display_name":"Akash Godbole","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Akash Godbole","raw_affiliation_strings":["Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0009-0000-3890-5591","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100613677","display_name":"Anil K. Jain","orcid":"https://orcid.org/0000-0002-6369-6995"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anil K. Jain","raw_affiliation_strings":["Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-6369-6995","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027893701"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":8.8781,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.98605736,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"19","issue":null,"first_page":"8428","last_page":"8440"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9961000084877014,"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":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7974798083305359},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4924331605434418},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.41982728242874146},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.41352713108062744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4061931371688843},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37898820638656616},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09119126200675964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7974798083305359},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4924331605434418},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.41982728242874146},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.41352713108062744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4061931371688843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37898820638656616},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09119126200675964}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2024.3413631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2024.3413631","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1995109806","https://openalex.org/W2046182649","https://openalex.org/W2063424920","https://openalex.org/W2114110317","https://openalex.org/W2126562928","https://openalex.org/W2130283969","https://openalex.org/W2148082513","https://openalex.org/W2159171257","https://openalex.org/W2159577413","https://openalex.org/W2160776381","https://openalex.org/W2196635279","https://openalex.org/W2559396463","https://openalex.org/W2606063865","https://openalex.org/W2796417745","https://openalex.org/W2946300279","https://openalex.org/W2962975612","https://openalex.org/W2969985801","https://openalex.org/W2990686905","https://openalex.org/W3006568837","https://openalex.org/W4205249317","https://openalex.org/W4205428640","https://openalex.org/W4220843729","https://openalex.org/W4220929574","https://openalex.org/W4239532633","https://openalex.org/W4309643846","https://openalex.org/W4312402191","https://openalex.org/W4312752593","https://openalex.org/W4312933868","https://openalex.org/W4316924395","https://openalex.org/W4320718476","https://openalex.org/W4321488197","https://openalex.org/W4376851402","https://openalex.org/W4382934573","https://openalex.org/W4383890556","https://openalex.org/W4385245566","https://openalex.org/W4385525529","https://openalex.org/W4385945608","https://openalex.org/W4386825547","https://openalex.org/W4386869644","https://openalex.org/W4387934883","https://openalex.org/W4389777367","https://openalex.org/W4392251497","https://openalex.org/W6631190155","https://openalex.org/W6757817989","https://openalex.org/W6793716030","https://openalex.org/W6800217721","https://openalex.org/W6847249830"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Contactless":[0],"palmprints":[1],"are":[2],"comprised":[3],"of":[4,85,119,156,163,178],"both":[5],"global":[6,17,35,68],"and":[7,36,57,67,88,97,110,147,196],"local":[8,20,37,66],"discriminative":[9],"features.":[10,69],"Most":[11],"prior":[12],"work":[13],"focuses":[14],"on":[15,135,149,167],"extracting":[16],"features":[18,21,38],"or":[19],"alone":[22],"for":[23,39,192],"palmprint":[24,41,74,94,131],"matching,":[25],"whereas":[26],"this":[27,50],"research":[28],"introduces":[29],"a":[30,53,58,71,93,117,129,161,168,175,189],"novel":[31],"framework":[32],"that":[33],"combines":[34],"enhanced":[40,193],"matching":[42,145],"accuracy.":[43],"Leveraging":[44],"recent":[45],"advancements":[46],"in":[47,133],"deep":[48],"learning,":[49],"study":[51],"integrates":[52],"vision":[54],"transformer":[55],"(ViT)":[56],"convolutional":[59],"neural":[60],"network":[61],"(CNN)":[62],"to":[63,80,115],"extract":[64,116],"complementary":[65],"Next,":[70],"mobile-based,":[72],"end-to-end":[73,180],"recognition":[75,184],"system":[76],"is":[77,186],"developed,":[78],"referred":[79],"as":[81],"Palm-ID.":[82],"On":[83],"top":[84],"the":[86,106,154,157,179,182],"ViT":[87],"CNN":[89],"features,":[90],"Palm-ID":[91,104],"incorporates":[92],"enhancement":[95],"module":[96],"efficient":[98],"dimensionality":[99],"reduction":[100],"(for":[101],"faster":[102],"matching).":[103],"balances":[105],"trade-off":[107],"between":[108],"accuracy":[109],"latency,":[111],"requiring":[112],"just":[113],"18ms":[114],"template":[118],"size":[120],"516":[121],"bytes,":[122],"which":[123],"can":[124],"be":[125],"efficiently":[126],"searched":[127],"against":[128],"10,000":[130],"gallery":[132],"0.33ms":[134],"an":[136],"AMD":[137],"EPYC":[138],"7543":[139],"32-Core":[140],"CPU":[141],"utilizing":[142],"128-threads.":[143],"Cross-database":[144],"protocols":[146],"evaluations":[148],"large-scale":[150],"operational":[151],"datasets":[152],"demonstrate":[153],"robustness":[155],"proposed":[158],"method,":[159],"achieving":[160],"TAR":[162],"98.06%":[164],"at":[165],"FAR=0.01%":[166],"newly":[169],"collected,":[170],"time-separated":[171],"dataset.":[172],"To":[173],"show":[174],"practical":[176],"deployment":[177],"system,":[181],"entire":[183],"pipeline":[185],"embedded":[187],"within":[188],"mobile":[190],"device":[191],"user":[194],"privacy":[195],"security.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":3}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
