{"id":"https://openalex.org/W2733399765","doi":"https://doi.org/10.1145/3093293.3093310","title":"A Decision Reliability Ratio Based Fusion Scheme for Biometric Verification","display_name":"A Decision Reliability Ratio Based Fusion Scheme for Biometric Verification","publication_year":2017,"publication_date":"2017-05-14","ids":{"openalex":"https://openalex.org/W2733399765","doi":"https://doi.org/10.1145/3093293.3093310","mag":"2733399765"},"language":"en","primary_location":{"id":"doi:10.1145/3093293.3093310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3093293.3093310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Bioinformatics and Biomedical Technology","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/A5112309245","display_name":"Liao Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liao Ni","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103617664","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-6515-740X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690915","display_name":"Shilei Liu","orcid":"https://orcid.org/0000-0002-9053-8458"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilei Liu","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074673170","display_name":"Houjun Huang","orcid":"https://orcid.org/0000-0003-0757-0949"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houjun Huang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397214","display_name":"Wenxin Li","orcid":"https://orcid.org/0000-0003-1744-7792"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Li","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.1748,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3193467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"16","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9451000094413757,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9413999915122986,"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/computer-science","display_name":"Computer science","score":0.7192070484161377},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.6964938044548035},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.687519371509552},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6771330237388611},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6469646096229553},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6067951917648315},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.5893106460571289},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5297331213951111},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.507138729095459},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4788817763328552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46759408712387085},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4338151514530182},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42136162519454956},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4099588096141815},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4071298837661743},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3931938707828522},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18224042654037476},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.11830168962478638},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09632530808448792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192070484161377},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.6964938044548035},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.687519371509552},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6771330237388611},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6469646096229553},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6067951917648315},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.5893106460571289},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5297331213951111},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.507138729095459},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4788817763328552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46759408712387085},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4338151514530182},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42136162519454956},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4099588096141815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4071298837661743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3931938707828522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18224042654037476},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.11830168962478638},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09632530808448792},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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":1,"locations":[{"id":"doi:10.1145/3093293.3093310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3093293.3093310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Bioinformatics and Biomedical Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324787","display_name":"Peking University","ror":"https://ror.org/02v51f717"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1991620112","https://openalex.org/W2004617923","https://openalex.org/W2019915615","https://openalex.org/W2034473161","https://openalex.org/W2036118277","https://openalex.org/W2078136378","https://openalex.org/W2086228340","https://openalex.org/W2102780391","https://openalex.org/W2114240988","https://openalex.org/W2118323481","https://openalex.org/W2121535649","https://openalex.org/W2136885397","https://openalex.org/W2157908585","https://openalex.org/W2171209378","https://openalex.org/W2510255217"],"related_works":["https://openalex.org/W2158491338","https://openalex.org/W2807901368","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W2606392311","https://openalex.org/W2320042380","https://openalex.org/W4385956668","https://openalex.org/W2900895161","https://openalex.org/W4380838366","https://openalex.org/W2539884462"],"abstract_inverted_index":{"Unimodal":[0],"biometric":[1],"verification":[2,26,135,166],"has":[3,72],"developed":[4],"a":[5,16,138],"lot":[6],"and":[7,102,143],"become":[8],"more":[9,64],"accurate,":[10],"but":[11,78],"there":[12],"is":[13,37,80,129],"still":[14],"not":[15,29],"perfect":[17],"algorithm.":[18],"In":[19],"the":[20,31,42,105,123,126,152,160,175,178,191],"meantime,":[21],"cases":[22],"exist":[23],"where":[24],"unimodal":[25],"system":[27],"could":[28,52,163],"meet":[30],"requirements":[32],"in":[33,83,155],"practical":[34],"use.":[35],"It":[36,172],"proved":[38],"that":[39],"algorithms":[40,61,136],"with":[41],"same":[43],"overall":[44],"accuracy":[45],"may":[46],"have":[47],"different":[48,73,120],"misclassified":[49],"patterns.":[50],"We":[51,92],"make":[53],"use":[54],"of":[55,125,140],"this":[56,79,90,100],"complementation":[57],"to":[58,68,98,130,170],"fuse":[59,131,151],"individual":[60],"together":[62],"for":[63],"precise":[65],"result.":[66],"According":[67],"our":[69],"observation,":[70],"algorithm":[71],"confidence":[74],"on":[75,89,119,137],"its":[76],"decisions":[77],"seldom":[81],"considered":[82],"fusion":[84,111,161,181],"methods.":[85],"Our":[86],"work":[87],"focuses":[88],"confidence.":[91],"first":[93],"define":[94],"decision":[95],"reliability":[96],"ratio":[97],"quantify":[99],"confidence,":[101],"then":[103],"propose":[104],"Maximum":[106],"Decision":[107],"Reliability":[108],"Ratio":[109],"(MDRR)":[110],"scheme":[112],"incorporating":[113],"Weighted":[114,185,187],"Voting.":[115],"Two":[116],"experiments":[117],"conducted":[118],"datasets":[121],"prove":[122],"effectiveness":[124],"method.":[127],"One":[128],"4":[132],"finger":[133],"vein":[134],"set":[139,154],"1000":[141],"fingers":[142],"5":[144],"images":[145],"per":[146],"finger.":[147],"The":[148],"other":[149],"experiment":[150],"multimodal":[153],"NIST-BSSR1.":[156],"Experiment":[157],"results":[158],"show":[159],"method":[162,194],"largely":[164],"improve":[165],"accuracy,":[167],"from":[168],"91.29%":[169],"99.81%.":[171],"also":[173],"shows":[174],"MDRR":[176],"outperforms":[177],"commonly":[179],"used":[180],"methods":[182],"as":[183],"Voting,":[184,186],"Sum":[188],"or":[189],"even":[190],"theoretically":[192],"optimal":[193],"Likelihood":[195],"Ratio-based":[196],"fusion.":[197]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
