{"id":"https://openalex.org/W2786852776","doi":"https://doi.org/10.1109/btas.2017.8272707","title":"Fingerprint pose estimation based on faster R-CNN","display_name":"Fingerprint pose estimation based on faster R-CNN","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2786852776","doi":"https://doi.org/10.1109/btas.2017.8272707","mag":"2786852776"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2017.8272707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5082029341","display_name":"Jiahong Ouyang","orcid":"https://orcid.org/0000-0002-0434-5757"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahong Ouyang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084679040","display_name":"Jianjiang Feng","orcid":"https://orcid.org/0000-0003-4971-6707"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjiang Feng","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460385","display_name":"Jiwen Lu","orcid":"https://orcid.org/0000-0002-6121-5529"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091834117","display_name":"Zhenhua Guo","orcid":"https://orcid.org/0000-0002-8201-0864"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Guo","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100620306","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0001-7701-234X"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["Graduate School at Shenzhen, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Graduate School at Shenzhen, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082029341"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.1095,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.80149037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"268","last_page":"276"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9995999932289124,"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":0.9995999932289124,"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/T11448","display_name":"Face recognition and analysis","score":0.9965000152587891,"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/T10992","display_name":"Forensic Anthropology and Bioarchaeology Studies","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.8145366907119751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7786914110183716},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.7733404636383057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7603583335876465},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.7514128684997559},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.668241024017334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6376931667327881},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5870676040649414},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5839966535568237},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4724864363670349},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.4526670575141907},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.45253121852874756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14181587100028992},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.10032859444618225},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06395140290260315}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8145366907119751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7786914110183716},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7733404636383057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7603583335876465},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.7514128684997559},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.668241024017334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6376931667327881},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5870676040649414},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5839966535568237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4724864363670349},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.4526670575141907},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.45253121852874756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14181587100028992},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.10032859444618225},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06395140290260315},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2017.8272707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"},{"id":"https://openalex.org/F4320335134","display_name":"National Institutes of Natural Sciences","ror":"https://ror.org/055n47h92"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1639795441","https://openalex.org/W1990088088","https://openalex.org/W2007394947","https://openalex.org/W2048887159","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2124995236","https://openalex.org/W2128530648","https://openalex.org/W2131461205","https://openalex.org/W2160367574","https://openalex.org/W2163605009","https://openalex.org/W2170075141","https://openalex.org/W2306842046","https://openalex.org/W2963037989","https://openalex.org/W3106250896","https://openalex.org/W4230579564","https://openalex.org/W6620707391","https://openalex.org/W6684191040","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2186585789","https://openalex.org/W3014822659","https://openalex.org/W4362496757","https://openalex.org/W2566091814","https://openalex.org/W4389371618","https://openalex.org/W2051501574","https://openalex.org/W2117826006","https://openalex.org/W2114937328","https://openalex.org/W2148654711","https://openalex.org/W2608025327"],"abstract_inverted_index":{"Fingerprint":[0],"pose":[1,18,46],"estimation":[2,19],"is":[3,50,122],"one":[4],"of":[5,8,17,116],"the":[6,54,68,78,88,95,111,114],"bottlenecks":[7],"indexing":[9,120],"in":[10],"large":[11],"scale":[12],"database.":[13],"The":[14],"existing":[15],"methods":[16],"are":[20,81,90,102],"based":[21,39],"on":[22,40,73],"manually":[23],"appointed":[24],"features":[25],"(e.g.":[26],"special":[27],"points,":[28],"ridges,":[29],"orientation":[30],"filed).":[31],"In":[32],"this":[33],"paper,":[34],"we":[35],"propose":[36],"a":[37,117],"method":[38],"deep":[41],"learning":[42],"to":[43,52,66,83],"achieve":[44],"accurate":[45],"estimation.":[47],"Faster":[48],"R-CNN":[49],"adopted":[51],"detect":[53],"center":[55],"point":[56],"and":[57,63,105],"rough":[58],"direction,":[59],"followed":[60],"by":[61,107],"intra-class":[62],"inter-class":[64],"combination":[65],"calculate":[67],"precise":[69],"direction.":[70],"Extensive":[71],"experiments":[72],"NIST-14":[74],"show":[75],"that":[76],"(1)":[77],"predicted":[79],"poses":[80,97],"close":[82],"manual":[84],"annotations":[85],"even":[86],"when":[87],"fingerprints":[89,109],"incomplete":[91],"or":[92],"noisy,":[93],"(2)":[94],"estimated":[96,112],"for":[98],"matching":[99],"fingerprint":[100,119],"pairs":[101],"very":[103],"consistent":[104],"(3)":[106],"registering":[108],"using":[110],"pose,":[113],"accuracy":[115],"state-of-the-art":[118],"system":[121],"further":[123],"improved.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}