{"id":"https://openalex.org/W3008876046","doi":"https://doi.org/10.1109/wacv45572.2020.9093397","title":"DeFraudNet:End2End Fingerprint Spoof Detection using Patch Level Attention","display_name":"DeFraudNet:End2End Fingerprint Spoof Detection using Patch Level Attention","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3008876046","doi":"https://doi.org/10.1109/wacv45572.2020.9093397","mag":"3008876046"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2002.08214","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112626249","display_name":"B. Anusha","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"B.V.S Anusha","raw_affiliation_strings":["IIT, Bombay","IIT, Bombay#TAB#"],"affiliations":[{"raw_affiliation_string":"IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"IIT, Bombay#TAB#","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072188872","display_name":"Sayan Banerjee","orcid":"https://orcid.org/0000-0002-8586-9236"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sayan Banerjee","raw_affiliation_strings":["IIT, Bombay","IIT, Bombay#TAB#"],"affiliations":[{"raw_affiliation_string":"IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"IIT, Bombay#TAB#","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016405213","display_name":"Subhasis Chaudhuri","orcid":"https://orcid.org/0000-0002-1680-0016"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhasis Chaudhuri","raw_affiliation_strings":["IIT, Bombay","Indian Institute of Technology Bombay"],"affiliations":[{"raw_affiliation_string":"IIT, Bombay","institution_ids":["https://openalex.org/I162827531"]},{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112626249"],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":0.6095,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.65111562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2684","last_page":"2693"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"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":1.0,"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":0.9907000064849854,"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/T10751","display_name":"Forensic and Genetic Research","score":0.9800000190734863,"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/computer-science","display_name":"Computer science","score":0.8054468631744385},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7202916145324707},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.6744658350944519},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6325140595436096},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5937334895133972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5579490065574646},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.5309146642684937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5243061780929565},{"id":"https://openalex.org/keywords/interoperability","display_name":"Interoperability","score":0.4327290654182434},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43029695749282837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8054468631744385},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7202916145324707},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.6744658350944519},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6325140595436096},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5937334895133972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5579490065574646},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.5309146642684937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5243061780929565},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.4327290654182434},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43029695749282837},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2002.08214","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.08214","pdf_url":"https://arxiv.org/pdf/2002.08214","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3008876046","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2002.08214.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2002.08214","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2002.08214","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2002.08214","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.08214","pdf_url":"https://arxiv.org/pdf/2002.08214","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6499999761581421,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320719","display_name":"Department of Science and Technology, Ministry of Science and Technology, India","ror":"https://ror.org/0101xrq71"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3008876046.pdf","grobid_xml":"https://content.openalex.org/works/W3008876046.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1551947943","https://openalex.org/W1578418902","https://openalex.org/W1686810756","https://openalex.org/W1781036881","https://openalex.org/W1979965748","https://openalex.org/W1980287119","https://openalex.org/W2008159608","https://openalex.org/W2020816142","https://openalex.org/W2032827811","https://openalex.org/W2071095136","https://openalex.org/W2090826149","https://openalex.org/W2095422257","https://openalex.org/W2097117768","https://openalex.org/W2097290407","https://openalex.org/W2103869071","https://openalex.org/W2136975665","https://openalex.org/W2141934703","https://openalex.org/W2151270693","https://openalex.org/W2163352848","https://openalex.org/W2194775991","https://openalex.org/W2215622264","https://openalex.org/W2302302587","https://openalex.org/W2304245051","https://openalex.org/W2492824679","https://openalex.org/W2531409750","https://openalex.org/W2550553598","https://openalex.org/W2612445135","https://openalex.org/W2741058322","https://openalex.org/W2771288630","https://openalex.org/W2884585870","https://openalex.org/W2891939671","https://openalex.org/W2910688461","https://openalex.org/W2937023704","https://openalex.org/W2948500402","https://openalex.org/W2949699261","https://openalex.org/W2956412927","https://openalex.org/W2963446712","https://openalex.org/W2963495494","https://openalex.org/W2964165334","https://openalex.org/W2970257772","https://openalex.org/W3005973417","https://openalex.org/W6633150018","https://openalex.org/W6638096550","https://openalex.org/W6674914833","https://openalex.org/W6687483927","https://openalex.org/W6688783732","https://openalex.org/W6725739302","https://openalex.org/W6728184133","https://openalex.org/W6737664043","https://openalex.org/W6746521738","https://openalex.org/W6753412334"],"related_works":["https://openalex.org/W3024829720","https://openalex.org/W1558778037","https://openalex.org/W1584545576","https://openalex.org/W2520487673","https://openalex.org/W3094117514","https://openalex.org/W3183950695","https://openalex.org/W3120619595","https://openalex.org/W3135085786","https://openalex.org/W2794701778","https://openalex.org/W2765507800","https://openalex.org/W2577692961","https://openalex.org/W2900664874","https://openalex.org/W2262108944","https://openalex.org/W2024439678","https://openalex.org/W3165529460","https://openalex.org/W1969793586","https://openalex.org/W2904347750","https://openalex.org/W2146126086","https://openalex.org/W2787609376","https://openalex.org/W2942062433"],"abstract_inverted_index":{"In":[0,28],"recent":[1],"years,":[2],"fingerprint":[3,36,85,93],"recognition":[4,37],"systems":[5],"have":[6],"made":[7],"remarkable":[8],"advancements":[9],"in":[10,22],"the":[11,35,49,119,181],"field":[12],"of":[13,30,67,145,168],"biometric":[14],"security":[15],"as":[16],"it":[17],"plays":[18],"an":[19,165],"important":[20],"role":[21],"personal,":[23],"national":[24],"and":[25,55,76,91,107,123,141,155,171,177,187,192],"global":[26,90],"security.":[27,51],"spite":[29],"all":[31],"these":[32,159],"notable":[33],"advancements,":[34],"technology":[38],"is":[39,115],"still":[40,60],"susceptible":[41],"to":[42,151],"spoof":[43,58,68,86],"attacks":[44],"which":[45,102],"can":[46],"significantly":[47,103],"jeopardize":[48],"user":[50],"The":[52,161],"cross":[53,56],"sensor":[54,74],"material":[57],"detection":[59,87],"pose":[61],"a":[62,65,81],"challenge":[63],"with":[64],"myriad":[66],"materials":[69],"emerging":[70],"every":[71],"day,":[72],"compromising":[73],"interoperability":[75],"robustness.":[77],"This":[78],"paper":[79],"proposes":[80],"novel":[82,111],"method":[83,131],"for":[84,117,125,189],"using":[88,100],"both":[89],"local":[92],"feature":[94],"descriptors.":[95],"These":[96],"descriptors":[97],"are":[98,148],"extracted":[99],"DenseNet":[101],"improves":[104],"cross-sensor,":[105,153],"cross-material":[106,154],"cross-dataset":[108,156],"performance.":[109],"A":[110,143],"patch":[112],"attention":[113],"network":[114,126],"used":[116],"finding":[118],"most":[120],"discriminative":[121],"patches":[122],"also":[124],"fusion.":[127],"We":[128],"evaluate":[129,152],"our":[130],"on":[132,173],"four":[133],"publicly":[134],"available":[135],"datasets:":[136],"LivDet":[137,174,190],"2011,":[138],"2013,":[139],"2015":[140,176,191],"2017.":[142],"set":[144],"comprehensive":[146],"experiments":[147],"carried":[149],"out":[150],"performance":[157],"over":[158],"datasets.":[160],"proposed":[162],"approach":[163],"achieves":[164],"average":[166],"accuracy":[167],"99.52%,":[169],"99.16%":[170],"99.72%":[172],"2017,":[175],"2011":[178,193],"respectively":[179],"outperforming":[180],"current":[182],"state-of-the-art":[183],"results":[184],"by":[185],"3%":[186],"4%":[188],"respectively.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}