{"id":"https://openalex.org/W2609818166","doi":"https://doi.org/10.1109/icpr.2016.7899755","title":"A novel fingerprint classification method based on deep learning","display_name":"A novel fingerprint classification method based on deep learning","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2609818166","doi":"https://doi.org/10.1109/icpr.2016.7899755","mag":"2609818166"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5065798206","display_name":"Ruxin Wang","orcid":"https://orcid.org/0000-0003-4772-3284"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruxin Wang","raw_affiliation_strings":["School of Mathematical Science, University of Chinese Academy of Sciences (UCAS), Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Science, University of Chinese Academy of Sciences (UCAS), Beijing","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046469888","display_name":"Congying Han","orcid":"https://orcid.org/0000-0002-3445-4620"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Congying Han","raw_affiliation_strings":["School of Mathematical Science, Key Laboratory of Big Data Mining and Knowledge Management, UCAS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Science, Key Laboratory of Big Data Mining and Knowledge Management, UCAS","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100561359","display_name":"Tiande Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tiande Guo","raw_affiliation_strings":["School of Mathematical Science, Key Laboratory of Big Data Mining and Knowledge Management, UCAS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Science, Key Laboratory of Big Data Mining and Knowledge Management, UCAS","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"931","last_page":"936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998000264167786,"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":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9901000261306763,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9883000254631042,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7894492149353027},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7653357982635498},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7164220809936523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7039111256599426},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6752169132232666},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5193648934364319},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5069718360900879},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49351322650909424},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4801763594150543},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.47312018275260925},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4523308575153351},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4490542709827423},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4363701343536377},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4197162389755249},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26375436782836914},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.17872586846351624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15739759802818298},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07147708535194397}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7894492149353027},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7653357982635498},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7164220809936523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7039111256599426},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6752169132232666},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5193648934364319},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5069718360900879},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49351322650909424},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4801763594150543},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.47312018275260925},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4523308575153351},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4490542709827423},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4363701343536377},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4197162389755249},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26375436782836914},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.17872586846351624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15739759802818298},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07147708535194397},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2016.7899755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/126101","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/126101","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W92913008","https://openalex.org/W1484721950","https://openalex.org/W1501535725","https://openalex.org/W1534649803","https://openalex.org/W1795776638","https://openalex.org/W1990590931","https://openalex.org/W1998808035","https://openalex.org/W2012611697","https://openalex.org/W2025768430","https://openalex.org/W2052655256","https://openalex.org/W2064312517","https://openalex.org/W2073660445","https://openalex.org/W2100495367","https://openalex.org/W2135426669","https://openalex.org/W2162642281","https://openalex.org/W2257979135","https://openalex.org/W2400801499","https://openalex.org/W2919115771","https://openalex.org/W4248506240"],"related_works":["https://openalex.org/W2807901368","https://openalex.org/W2158491338","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W2606392311","https://openalex.org/W4385956668","https://openalex.org/W2900895161","https://openalex.org/W4380838366","https://openalex.org/W2376543359","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Fingerprint":[0],"classification":[1,59,79,102,108,128],"is":[2,29,129,133,138,144],"an":[3,30],"effective":[4],"technique":[5],"for":[6,106],"reducing":[7],"the":[8,14,56,63,70,78,86,96,113,120,125,152],"candidate":[9],"numbers":[10],"of":[11,16,115,127],"fingerprints":[12],"in":[13,18,38,95],"stage":[15],"matching":[17],"automatic":[19],"fingerprint":[20,58],"identification":[21],"system":[22],"(AFIS).":[23],"In":[24,47],"recent":[25],"years,":[26],"deep":[27],"learning":[28],"emerging":[31],"technology":[32],"which":[33,109],"has":[34],"achieved":[35],"great":[36],"success":[37],"many":[39],"fields,":[40],"such":[41],"as":[42,77],"image":[43],"processing,":[44],"computer":[45],"vision.":[46],"this":[48],"paper,":[49],"we":[50,81,123,155],"have":[51],"a":[52,147],"preliminary":[53],"attempt":[54],"on":[55,62],"traditional":[57],"problem":[60],"based":[61],"new":[64],"depth":[65],"neural":[66],"network":[67],"method.":[68],"For":[69],"four-class":[71],"problem,":[72],"only":[73,118],"choosing":[74],"orientation":[75],"field":[76],"feature,":[80],"achieve":[82],"91.4%":[83],"accuracy":[84,114,126],"using":[85],"stacked":[87],"sparse":[88],"autoencoders":[89],"(SAE)":[90],"with":[91,146],"three":[92],"hidden":[93],"layers":[94],"NIST-DB4":[97],"database.":[98],"And":[99],"then":[100],"two":[101],"probabilities":[103],"are":[104],"used":[105],"fuzzy":[107,153],"can":[110],"effectively":[111],"enhance":[112],"classification.":[116],"By":[117],"adjusting":[119],"probability":[121],"threshold,":[122],"get":[124],"96.1%":[130],"(setting":[131,136,142],"threshold":[132,137,143],"0.85),":[134],"97.2%":[135],"0.90)":[139],"and":[140],"98.0%":[141],"0.95)":[145],"single":[148],"layer":[149],"SAE.":[150],"Applying":[151],"method,":[154],"obtain":[156],"higher":[157],"accuracy.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}