{"id":"https://openalex.org/W2170780759","doi":"https://doi.org/10.1109/ijcnn.2008.4633967","title":"Fusion of biometric systems using one-class classification","display_name":"Fusion of biometric systems using one-class classification","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2170780759","doi":"https://doi.org/10.1109/ijcnn.2008.4633967","mag":"2170780759"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4633967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5102165386","display_name":"Cheila Bergamini","orcid":null},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Cheila Bergamini","raw_affiliation_strings":["Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil"],"affiliations":[{"raw_affiliation_string":"Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038884704","display_name":"Luiz S. Oliveira","orcid":"https://orcid.org/0000-0002-0595-5370"},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luiz S. Oliveira","raw_affiliation_strings":["Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil"],"affiliations":[{"raw_affiliation_string":"Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074262951","display_name":"Alessandro L. Koerich","orcid":"https://orcid.org/0000-0001-5879-7014"},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alessandro L. Koerich","raw_affiliation_strings":["Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil"],"affiliations":[{"raw_affiliation_string":"Pontifical Catholic University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026340083","display_name":"Robert Sabourin","orcid":"https://orcid.org/0000-0002-9098-1011"},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Robert Sabourin","raw_affiliation_strings":["Ecole de Technologie Sup\u00e9rieure, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"Ecole de Technologie Sup\u00e9rieure, Montreal, Canada","institution_ids":["https://openalex.org/I9736820"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102165386"],"corresponding_institution_ids":["https://openalex.org/I176838256"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20630783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"20","issue":null,"first_page":"1308","last_page":"1313"},"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":0.9948999881744385,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.97079998254776,"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/biometrics","display_name":"Biometrics","score":0.7916218042373657},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.703426718711853},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7020035982131958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6881844401359558},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6740437746047974},{"id":"https://openalex.org/keywords/one-class-classification","display_name":"One-class classification","score":0.6594374775886536},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6567829847335815},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5630595684051514},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46141088008880615},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4387866258621216},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41606613993644714}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7916218042373657},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.703426718711853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7020035982131958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881844401359558},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6740437746047974},{"id":"https://openalex.org/C34872919","wikidata":"https://www.wikidata.org/wiki/Q7092302","display_name":"One-class classification","level":3,"score":0.6594374775886536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6567829847335815},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5630595684051514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46141088008880615},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4387866258621216},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41606613993644714}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2008.4633967","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4633967","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.140.6808","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.6808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ppgia.pucpr.br/~alekoe/Papers/ALEKOE-IJCNN2008.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W740415","https://openalex.org/W3035862","https://openalex.org/W1488833649","https://openalex.org/W1563088657","https://openalex.org/W1622922661","https://openalex.org/W1944395034","https://openalex.org/W1970655212","https://openalex.org/W1980527312","https://openalex.org/W1991792143","https://openalex.org/W2014235936","https://openalex.org/W2061272711","https://openalex.org/W2063504114","https://openalex.org/W2100294832","https://openalex.org/W2105888616","https://openalex.org/W2109088898","https://openalex.org/W2118424019","https://openalex.org/W2121292316","https://openalex.org/W2127775588","https://openalex.org/W2132870739","https://openalex.org/W2137130182","https://openalex.org/W2156909104","https://openalex.org/W2165956633","https://openalex.org/W4362236847","https://openalex.org/W6636686524","https://openalex.org/W6677310826"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W2095239294","https://openalex.org/W3147744369","https://openalex.org/W4241440711","https://openalex.org/W2062586268","https://openalex.org/W2019582947","https://openalex.org/W3212688212","https://openalex.org/W4300873085"],"abstract_inverted_index":{"One":[0],"of":[1,5,11],"the":[2,9,35,41,55,61,81,105,112],"main":[3],"requirements":[4],"biometric":[6,28,77],"systems":[7],"is":[8,83,92],"ability":[10],"producing":[12],"very":[13,19],"low":[14],"false":[15],"acceptation":[16],"rate,":[17],"which":[18],"often":[20],"can":[21],"be":[22,71],"achieved":[23],"only":[24],"by":[25],"combining":[26],"different":[27],"traits.":[29],"The":[30,94],"literature":[31],"has":[32],"shown":[33],"that":[34,67],"pattern":[36,56],"classification":[37,57,63,69,98],"approach":[38,44],"usually":[39],"surpasses":[40,110],"classifier":[42,114],"combination":[43,115],"for":[45,76,96],"this":[46,49,101],"task.":[47],"In":[48],"work":[50],"we":[51],"take":[52],"into":[53],"account":[54],"approach,":[58],"but":[59],"considering":[60],"one-class":[62,68,97],"approach.":[64],"We":[65],"show":[66],"could":[70],"considered":[72],"as":[73],"an":[74],"alternative":[75],"fusion":[78],"specially":[79],"when":[80],"data":[82,87],"highly":[84],"unbalanced":[85],"or":[86],"from":[88],"a":[89],"single":[90],"class":[91],"available.":[93],"results":[95],"reported":[99],"in":[100],"paper":[102],"compares":[103],"to":[104],"standard":[106],"two-class":[107],"SVM":[108],"and":[109],"all":[111],"conventional":[113],"rules":[116],"tested.":[117]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
