{"id":"https://openalex.org/W7128485995","doi":"https://doi.org/10.1109/tai.2026.3662649","title":"Learning From Easy to Hard: Fingerprint Spoof Detection With Hard Sample Mining","display_name":"Learning From Easy to Hard: Fingerprint Spoof Detection With Hard Sample Mining","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128485995","doi":"https://doi.org/10.1109/tai.2026.3662649"},"language":null,"primary_location":{"id":"doi:10.1109/tai.2026.3662649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2026.3662649","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"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 Artificial Intelligence","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/A5037469847","display_name":"Wenny Ramadha Putri","orcid":"https://orcid.org/0000-0002-5456-160X"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wenny Ramadha Putri","raw_affiliation_strings":["National Central University"],"raw_orcid":"https://orcid.org/0000-0002-5456-160X","affiliations":[{"raw_affiliation_string":"National Central University","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093294188","display_name":"Farchan Raswa Hakim","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Farchan Raswa Hakim","raw_affiliation_strings":["National Central University"],"raw_orcid":"https://orcid.org/0009-0008-3656-9107","affiliations":[{"raw_affiliation_string":"National Central University","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030387126","display_name":"Bach-Tung Pham","orcid":null},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bach-Tung Pham","raw_affiliation_strings":["National Central University"],"raw_orcid":"https://orcid.org/0009-0004-8985-1086","affiliations":[{"raw_affiliation_string":"National Central University","institution_ids":["https://openalex.org/I22265921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125592429","display_name":"Shang-Kuan Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]},{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shang-Kuan Chen","raw_affiliation_strings":["Chung Yuan Christian University","Yuan Ze University"],"raw_orcid":"https://orcid.org/0000-0002-5879-4048","affiliations":[{"raw_affiliation_string":"Chung Yuan Christian University","institution_ids":["https://openalex.org/I151221077"]},{"raw_affiliation_string":"Yuan Ze University","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102604318","display_name":"Chung-I Huang","orcid":"https://orcid.org/0009-0004-5266-2900"},"institutions":[{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]},{"id":"https://openalex.org/I99613584","display_name":"National Taipei University","ror":"https://ror.org/03e29r284","country_code":"TW","type":"education","lineage":["https://openalex.org/I99613584"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chung-I Huang","raw_affiliation_strings":["National Chung Hsing University"],"raw_orcid":"https://orcid.org/0009-0004-5266-2900","affiliations":[{"raw_affiliation_string":"National Chung Hsing University","institution_ids":["https://openalex.org/I162838928","https://openalex.org/I99613584"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125565753","display_name":"Kuo-Chen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kuo-Chen Li","raw_affiliation_strings":["Chung Yuan Christian University"],"raw_orcid":"https://orcid.org/0000-0002-0110-5491","affiliations":[{"raw_affiliation_string":"Chung Yuan Christian University","institution_ids":["https://openalex.org/I151221077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025762419","display_name":"Shih\u2010Lun Chen","orcid":"https://orcid.org/0000-0002-4079-9350"},"institutions":[{"id":"https://openalex.org/I151221077","display_name":"Chung Yuan Christian University","ror":"https://ror.org/02w8ws377","country_code":"TW","type":"education","lineage":["https://openalex.org/I151221077"]},{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shih-Lun Chen","raw_affiliation_strings":["Chung Yuan Christian University","Yuan Ze University"],"raw_orcid":"https://orcid.org/0000-0002-4079-9350","affiliations":[{"raw_affiliation_string":"Chung Yuan Christian University","institution_ids":["https://openalex.org/I151221077"]},{"raw_affiliation_string":"Yuan Ze University","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029325015","display_name":"Jia\u2010Ching Wang","orcid":"https://orcid.org/0000-0003-0024-6732"},"institutions":[{"id":"https://openalex.org/I22265921","display_name":"National Central University","ror":"https://ror.org/00944ve71","country_code":"TW","type":"education","lineage":["https://openalex.org/I22265921"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Ching Wang","raw_affiliation_strings":["National Central University"],"raw_orcid":"https://orcid.org/0000-0003-0024-6732","affiliations":[{"raw_affiliation_string":"National Central University","institution_ids":["https://openalex.org/I22265921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"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":0.14776793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"8","first_page":"4367","last_page":"4375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9904000163078308,"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":0.9904000163078308,"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":0.002099999925121665,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.0005000000237487257,"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/discriminative-model","display_name":"Discriminative model","score":0.8187000155448914},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7990999817848206},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5605999827384949},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4779999852180481},{"id":"https://openalex.org/keywords/spoofing-attack","display_name":"Spoofing attack","score":0.4708999991416931},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.42579999566078186},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.38850000500679016}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8187000155448914},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7990999817848206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7610999941825867},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6460999846458435},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5605999827384949},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C167900197","wikidata":"https://www.wikidata.org/wiki/Q11081100","display_name":"Spoofing attack","level":2,"score":0.4708999991416931},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4474000036716461},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.42579999566078186},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.38850000500679016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3043999969959259},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C67174900","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Minutiae","level":4,"score":0.2777999937534332},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C164995936","wikidata":"https://www.wikidata.org/wiki/Q5450283","display_name":"Fingerprint Verification Competition","level":4,"score":0.25699999928474426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2026.3662649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2026.3662649","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"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 Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7091991901397705,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2008056655","https://openalex.org/W2112796928","https://openalex.org/W2151270693","https://openalex.org/W2194775991","https://openalex.org/W2215622264","https://openalex.org/W2304245051","https://openalex.org/W2492824679","https://openalex.org/W2741058322","https://openalex.org/W2792557137","https://openalex.org/W2956767096","https://openalex.org/W2962750014","https://openalex.org/W2962858109","https://openalex.org/W2963248893","https://openalex.org/W2975485695","https://openalex.org/W3023066750","https://openalex.org/W3109894131","https://openalex.org/W3125611483","https://openalex.org/W4210971432","https://openalex.org/W4313182973","https://openalex.org/W4321609502","https://openalex.org/W4321609509","https://openalex.org/W4377082039","https://openalex.org/W4381327782","https://openalex.org/W4382466430","https://openalex.org/W4383893982","https://openalex.org/W4385461365","https://openalex.org/W4385605940","https://openalex.org/W4386066407","https://openalex.org/W4386120722","https://openalex.org/W4386799357","https://openalex.org/W4386869644","https://openalex.org/W4396523410","https://openalex.org/W4396845034","https://openalex.org/W4400688817","https://openalex.org/W4402435345","https://openalex.org/W4403658434","https://openalex.org/W4403878234","https://openalex.org/W7133237037"],"related_works":[],"abstract_inverted_index":{"To":[0],"counter":[1],"unauthorized":[2],"access":[3],"posed":[4],"by":[5],"presentation":[6],"attacks":[7],"in":[8,143],"fingerprint":[9,14,59,128,144],"authentication":[10],"systems,":[11],"deep":[12],"learning-based":[13],"spoofing":[15],"detection":[16,61],"methods":[17,142],"have":[18],"been":[19],"introduced.":[20],"However,":[21],"different":[22],"artificial":[23],"materials":[24],"produce":[25],"non-uniform":[26],"spoof":[27,60,127,145],"image":[28],"representations,":[29],"leading":[30],"to":[31,90,102,117],"a":[32,49,57,72,77,97,119],"bias":[33],"toward":[34],"easy-to-recognize":[35],"samples":[36,106,129],"while":[37],"ignoring":[38],"hard-to-recognize":[39],"ones.":[40],"Hard":[41,98],"sample":[42,65],"mining":[43,66],"is":[44,80,88,149],"beneficial":[45],"for":[46,107,123],"accurately":[47],"modeling":[48],"discriminative":[50,121],"function.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55],"propose":[56],"novel":[58],"method":[62],"with":[63],"hard":[64,93,105],"called":[67],"EasyHard-FSD.":[68],"Specifically,":[69],"EasyHard-FSD":[70,95,139],"introduces":[71],"self-training":[73],"(teacher/student":[74],"model),":[75],"where":[76],"teacher":[78],"model":[79,116],"learned":[81],"using":[82],"all":[83],"original":[84],"samples,":[85],"and":[86,126,135],"it":[87],"used":[89],"identify":[91],"possible":[92],"samples.":[94],"employs":[96],"Mining":[99],"Module":[100],"(HMM)":[101],"mask":[103],"out":[104],"the":[108,114],"student":[109,115],"model.":[110],"This":[111],"strategy":[112],"allows":[113],"learn":[118],"better":[120],"function":[122],"recognizing":[124],"live":[125],"accurately.":[130],"Experimental":[131],"results":[132],"on":[133],"LiveDet2013":[134],"LiveDet2015":[136],"demonstrate":[137],"that":[138],"outperforms":[140],"state-of-the-art":[141],"detection.":[146],"Our":[147],"code":[148],"publicly":[150],"available":[151],"athttps://github.com/lalakitchen/EasyHard-FSD.":[152]},"counts_by_year":[],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-02-11T00:00:00"}