{"id":"https://openalex.org/W4416148996","doi":"https://doi.org/10.1109/tifs.2025.3632226","title":"AdVeinSAM: Adversarial Learning-Based Large Model for Palm-Vein Feature Segmentation","display_name":"AdVeinSAM: Adversarial Learning-Based Large Model for Palm-Vein Feature Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416148996","doi":"https://doi.org/10.1109/tifs.2025.3632226"},"language":null,"primary_location":{"id":"doi:10.1109/tifs.2025.3632226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3632226","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/A5054571269","display_name":"Huafeng Qin","orcid":"https://orcid.org/0000-0003-4911-0393"},"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":["National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090004026","display_name":"Henghua Deng","orcid":"https://orcid.org/0009-0009-3049-9192"},"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":"Hulei Deng","raw_affiliation_strings":["School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China"],"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/A5012796533","display_name":"Hailong Hu","orcid":"https://orcid.org/0000-0001-5138-4014"},"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":"Hailong Hu","raw_affiliation_strings":["National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"National Research Base of Intelligent Manufacturing Service, 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"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"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/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"],"affiliations":[{"raw_affiliation_string":"SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris, Palaiseau, France","institution_ids":["https://openalex.org/I4210145102"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054571269"],"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":0.44685876,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"12285","last_page":"12300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9307000041007996,"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":0.9307000041007996,"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/T11866","display_name":"Reconstructive Facial Surgery Techniques","score":0.015599999576807022,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.0071000000461936,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7432000041007996},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5788999795913696},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.572700023651123},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.47690001130104065},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4717999994754791},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46619999408721924},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4401000142097473},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.41760000586509705},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4174000024795532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8014000058174133},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7432000041007996},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5788999795913696},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.572700023651123},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5175999999046326},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.47690001130104065},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4717999994754791},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4401000142097473},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.41760000586509705},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4174000024795532},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.3046000003814697},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3001999855041504},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27160000801086426},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2025.3632226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2025.3632226","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":84,"referenced_works":["https://openalex.org/W1512403036","https://openalex.org/W1963920031","https://openalex.org/W1974727132","https://openalex.org/W1974821667","https://openalex.org/W1991620112","https://openalex.org/W1997175872","https://openalex.org/W2004617923","https://openalex.org/W2014470493","https://openalex.org/W2023631753","https://openalex.org/W2030754587","https://openalex.org/W2031337792","https://openalex.org/W2039536345","https://openalex.org/W2043229217","https://openalex.org/W2051075456","https://openalex.org/W2067400486","https://openalex.org/W2071337748","https://openalex.org/W2072700947","https://openalex.org/W2102780391","https://openalex.org/W2114122776","https://openalex.org/W2118323481","https://openalex.org/W2119416456","https://openalex.org/W2122790104","https://openalex.org/W2144025519","https://openalex.org/W2160776381","https://openalex.org/W2302255633","https://openalex.org/W2325939864","https://openalex.org/W2407362091","https://openalex.org/W2513262855","https://openalex.org/W2552954853","https://openalex.org/W2584959338","https://openalex.org/W2598896220","https://openalex.org/W2599632008","https://openalex.org/W2604853352","https://openalex.org/W2787357964","https://openalex.org/W2811014381","https://openalex.org/W2899436599","https://openalex.org/W2917172368","https://openalex.org/W2919938126","https://openalex.org/W2942413398","https://openalex.org/W2956862036","https://openalex.org/W2962914239","https://openalex.org/W2963111219","https://openalex.org/W2985990156","https://openalex.org/W2996162755","https://openalex.org/W3003423830","https://openalex.org/W3005476017","https://openalex.org/W3007827444","https://openalex.org/W3026918854","https://openalex.org/W3046220160","https://openalex.org/W3092623934","https://openalex.org/W3094777611","https://openalex.org/W3132400026","https://openalex.org/W3134449933","https://openalex.org/W3142024888","https://openalex.org/W3202353095","https://openalex.org/W3204321367","https://openalex.org/W4213014045","https://openalex.org/W4214550350","https://openalex.org/W4214768171","https://openalex.org/W4225683910","https://openalex.org/W4285175773","https://openalex.org/W4292787462","https://openalex.org/W4312820255","https://openalex.org/W4322766882","https://openalex.org/W4323065905","https://openalex.org/W4360993699","https://openalex.org/W4366452639","https://openalex.org/W4377007929","https://openalex.org/W4379929801","https://openalex.org/W4385127856","https://openalex.org/W4386075975","https://openalex.org/W4387717594","https://openalex.org/W4388819810","https://openalex.org/W4389428762","https://openalex.org/W4390874575","https://openalex.org/W4393184772","https://openalex.org/W4398151247","https://openalex.org/W4399357306","https://openalex.org/W4400448268","https://openalex.org/W4401386967","https://openalex.org/W4401725766","https://openalex.org/W4401819803","https://openalex.org/W4408267899","https://openalex.org/W4408634392"],"related_works":[],"abstract_inverted_index":{"Palm-vein":[0],"recognition":[1,10],"is":[2,18],"gaining":[3],"significant":[4],"attention":[5],"as":[6,35,64,66],"a":[7,28,179],"high-security":[8],"biometric":[9],"technology.":[11],"However,":[12],"the":[13,54,59,118,123,135,146,167,172,192,197,208,211,220,228,246,265,273,288],"vein":[14,25,83,111,119,159,181,198],"image":[15,45,124,193,221],"acquisition":[16],"process":[17],"easily":[19],"affected":[20],"by":[21,115],"several":[22],"factors,":[23],"making":[24],"texture":[26,84,100,189,296],"segmentation":[27,46,120,173,182,199,229,249],"challenging":[29,224,242],"task.":[30],"Recently,":[31],"foundation":[32],"models":[33,108],"such":[34],"Segment":[36],"Anything":[37],"Model":[38],"(SAM)":[39,176],"have":[40],"shown":[41],"remarkable":[42],"potential":[43],"in":[44,294],"without":[47],"requiring":[48],"prior":[49],"retraining.":[50],"Nevertheless,":[51],"due":[52],"to":[53,80,109,138,151,170,204,226,244],"large":[55,96,107,136],"domain":[56],"discrepancy":[57],"between":[58],"resource":[60],"and":[61,122,157,177,196,210,248,260,282,290],"target":[62],"domains,":[63],"well":[65],"limited":[67],"datasets,":[68],"existing":[69],"solutions":[70],"that":[71,264],"rely":[72],"heavily":[73],"on":[74,255],"abundant":[75],"training":[76,129],"images":[77,160],"often":[78],"struggle":[79],"extract":[81],"robust":[82,237],"patterns.":[85],"To":[86],"address":[87],"this":[88],"challenge,":[89],"we":[90,144,165],"propose":[91],"AdVeinSAM,":[92,206],"an":[93],"adversarial":[94,217],"learning-based":[95],"model":[97,121,137,169,175,183,200,268],"for":[98,161,231],"palm-vein":[99,188,258,295],"extraction,":[101],"which":[102,154,185],"leverages":[103],"rich":[104],"knowledge":[105,133],"of":[106,279,292],"enhance":[110,139],"pattern":[112],"segmentation.":[113],"Specifically,":[114],"alternately":[116],"optimizing":[117],"generator,":[125],"AdVeinSAM":[126,267,293],"generates":[127,155,223],"diverse":[128,156],"samples,":[130],"effectively":[131,186],"transferring":[132],"from":[134,240],"feature":[140,238],"extraction":[141],"robustness.":[142],"First,":[143],"incorporate":[145],"wavelet":[147],"transform":[148],"into":[149],"xLSTM-UNet":[150],"design":[152],"Wavelet-xLSTM-UNet,":[153],"realistic":[158],"data":[162],"augmentation.":[163],"Then,":[164],"improve":[166,245],"NOLA":[168],"fine-tune":[171],"anything":[174],"develop":[178],"specialized":[180],"(VeinSAM),":[184],"extracts":[187],"features.":[190],"Finally,":[191],"generator":[194,209,222],"(Wavelet-xLSTM-UNet)":[195],"(VeinSAM)":[201],"are":[202,213],"combined":[203],"form":[205],"where":[207],"VeinSAM":[212,234],"alternatively":[214],"updated":[215],"through":[216],"training.":[218],"Concretely,":[219],"samples":[225,243],"increase":[227],"difficulty":[230],"VeinSAM,":[232],"while":[233],"learns":[235],"more":[236],"representations":[239],"these":[241],"generalization":[247],"accuracy.":[250],"We":[251],"conduct":[252],"extensive":[253],"experiments":[254],"three":[256],"public":[257],"databases":[259],"experimental":[261],"results":[262,286],"demonstrate":[263],"proposed":[266],"outperforms":[269],"state-of-the-art":[270],"solutions,":[271],"achieving":[272],"lowest":[274],"equal":[275],"error":[276],"rates":[277],"(EERs)":[278],"1.48%,":[280],"4.76%,":[281],"0.72%,":[283],"respectively.":[284],"These":[285],"confirm":[287],"effectiveness":[289],"robustness":[291],"extraction.":[297]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-12T00:00:00"}