{"id":"https://openalex.org/W7133360369","doi":"https://doi.org/10.1109/ijcb65343.2025.11411553","title":"Saliency-Guided Training for Fingerprint Presentation Attack Detection","display_name":"Saliency-Guided Training for Fingerprint Presentation Attack Detection","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133360369","doi":"https://doi.org/10.1109/ijcb65343.2025.11411553"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11411553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-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/A5102061442","display_name":"Samuel Webster","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samuel Webster","raw_affiliation_strings":["University of Notre Dame,Department of Computer Science and Engineering,IN,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame,Department of Computer Science and Engineering,IN,USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121423204","display_name":"Adam Czajka","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Czajka","raw_affiliation_strings":["University of Notre Dame,Department of Computer Science and Engineering,IN,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame,Department of Computer Science and Engineering,IN,USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66351741,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.8450999855995178,"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":0.8450999855995178,"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":0.018699999898672104,"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/T11448","display_name":"Face recognition and analysis","score":0.016699999570846558,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/fingerprint","display_name":"Fingerprint (computing)","score":0.8051999807357788},{"id":"https://openalex.org/keywords/liveness","display_name":"Liveness","score":0.7597000002861023},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7123000025749207},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.7062000036239624},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5845999717712402},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5658000111579895}],"concepts":[{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.8051999807357788},{"id":"https://openalex.org/C15569618","wikidata":"https://www.wikidata.org/wiki/Q3561421","display_name":"Liveness","level":2,"score":0.7597000002861023},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7123000025749207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089999914169312},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7062000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7002000212669373},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5845999717712402},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.4652000069618225},{"id":"https://openalex.org/C164995936","wikidata":"https://www.wikidata.org/wiki/Q5450283","display_name":"Fingerprint Verification Competition","level":4,"score":0.4487999975681305},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41280001401901245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3402000069618225},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29580000042915344}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11411553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411553","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.44860929250717163,"display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1974072979","https://openalex.org/W1986702455","https://openalex.org/W2080179063","https://openalex.org/W2166266107","https://openalex.org/W2215622264","https://openalex.org/W2295107390","https://openalex.org/W2304245051","https://openalex.org/W2553683761","https://openalex.org/W2602244503","https://openalex.org/W2769360815","https://openalex.org/W2787714893","https://openalex.org/W2792557137","https://openalex.org/W2907757105","https://openalex.org/W2951639392","https://openalex.org/W2956767096","https://openalex.org/W2963446712","https://openalex.org/W2964009128","https://openalex.org/W2964165334","https://openalex.org/W3005670606","https://openalex.org/W3005991297","https://openalex.org/W3017988947","https://openalex.org/W3162881418","https://openalex.org/W3186086436","https://openalex.org/W3208614786","https://openalex.org/W4319300000","https://openalex.org/W4319300047","https://openalex.org/W4389232535","https://openalex.org/W4392411875","https://openalex.org/W4394625686","https://openalex.org/W4402352414","https://openalex.org/W4404238914"],"related_works":[],"abstract_inverted_index":{"Saliency-guided":[0],"training,":[1],"which":[2],"directs":[3],"model":[4,130],"learning":[5],"to":[6,29,37,78,142,144,162],"important":[7],"regions":[8],"of":[9,41,82,94,113],"images,":[10],"has":[11],"demonstrated":[12],"generalization":[13,131],"improvements":[14],"across":[15],"various":[16,71],"biometric":[17],"presentation":[18],"attack":[19],"detection":[20],"(PAD)":[21],"tasks.":[22],"This":[23],"paper":[24,161],"presents":[25],"its":[26,133,140],"first":[27,116],"application":[28],"fingerprint":[30,44,98,148],"PAD.":[31,149],"We":[32],"conducted":[33],"a":[34,39,110],"50-participant":[35],"study":[36],"create":[38],"dataset":[40],"800":[42],"human-annotated":[43],"perceptually-important":[45],"maps,":[46],"explored":[47],"alongside":[48],"algorithmically-generated":[49],"\"pseudosaliency,\"":[50],"including":[51],"minutiae-based,":[52],"image":[53],"quality-based,":[54],"and":[55,87,103,107,139,154],"autoencoder-based":[56],"saliency":[57,152],"maps.":[58],"Evaluating":[59],"on":[60,85,118],"the":[61,80,92,115,119,160],"2021":[62],"Fingerprint":[63],"Liveness":[64],"Detection":[65],"Competition":[66],"testing":[67],"set,":[68],"we":[69,108],"explore":[70],"configurations":[72],"within":[73],"five":[74],"distinct":[75],"training":[76,84,96],"scenarios":[77],"assess":[79],"impact":[81],"saliency-guided":[83,95,125],"accuracy":[86],"generalization.":[88],"Our":[89,122],"findings":[90],"demonstrate":[91],"effectiveness":[93,134],"for":[97,128],"PAD":[99],"in":[100,147],"both":[101],"limited":[102],"large":[104],"data":[105,136,153],"contexts,":[106],"present":[109],"configuration":[111],"capable":[112],"earning":[114],"place":[117],"LivDet-2021":[120],"benchmark.":[121],"results":[123],"highlight":[124],"training\u2019s":[126],"promise":[127],"increased":[129],"capabilities,":[132],"when":[135],"is":[137],"limited,":[138],"potential":[141],"scale":[143],"larger":[145],"datasets":[146],"All":[150],"collected":[151],"trained":[155],"models":[156],"are":[157],"released":[158],"with":[159],"support":[163],"reproducible":[164],"research.":[165]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
