{"id":"https://openalex.org/W2011412442","doi":"https://doi.org/10.1142/s0218001408006314","title":"CLASSIFIER COMBINATION AND ITS APPLICATION IN IRIS RECOGNITION","display_name":"CLASSIFIER COMBINATION AND ITS APPLICATION IN IRIS RECOGNITION","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2011412442","doi":"https://doi.org/10.1142/s0218001408006314","mag":"2011412442"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001408006314","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001408006314","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5026802745","display_name":"Xinhua Feng","orcid":null},"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":"XINHUA FENG","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111444853","display_name":"Xiaoqing Ding","orcid":null},"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":"XIAOQING DING","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100821520","display_name":"Youshou Wu","orcid":null},"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":"YOUSHOU WU","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing 100084, P. R. China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077075722","display_name":"Patrick S. P. Wang","orcid":"https://orcid.org/0000-0002-9336-3155"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"PATRICK S. P. WANG","raw_affiliation_strings":["College of Computer and Information Science, Northeastern University Boston, MA 02115, USA","College of Computer and Information Science, Northeastern University, Boston, MA 02115, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Northeastern University Boston, MA 02115, USA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"College of Computer and Information Science, Northeastern University, Boston, MA 02115, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5145,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9473232,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"22","issue":"03","first_page":"617","last_page":"638"},"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/T11800","display_name":"User Authentication and Security Systems","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9519000053405762,"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/classifier","display_name":"Classifier (UML)","score":0.8229732513427734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7225531935691833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6946086287498474},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6634471416473389},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.6526961922645569},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6408612728118896},{"id":"https://openalex.org/keywords/margin-classifier","display_name":"Margin classifier","score":0.5692905783653259},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.441975474357605},{"id":"https://openalex.org/keywords/quadratic-classifier","display_name":"Quadratic classifier","score":0.43812069296836853}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.8229732513427734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7225531935691833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6946086287498474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6634471416473389},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.6526961922645569},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6408612728118896},{"id":"https://openalex.org/C173102733","wikidata":"https://www.wikidata.org/wiki/Q6760396","display_name":"Margin classifier","level":3,"score":0.5692905783653259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.441975474357605},{"id":"https://openalex.org/C52620605","wikidata":"https://www.wikidata.org/wiki/Q7268357","display_name":"Quadratic classifier","level":3,"score":0.43812069296836853}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001408006314","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001408006314","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1974821667","https://openalex.org/W2008338741","https://openalex.org/W2014470493","https://openalex.org/W2061272711","https://openalex.org/W2102796633","https://openalex.org/W2114212719","https://openalex.org/W2140959843","https://openalex.org/W2158275940","https://openalex.org/W2169504763","https://openalex.org/W2171759622","https://openalex.org/W2309693750"],"related_works":["https://openalex.org/W1483596504","https://openalex.org/W2010370304","https://openalex.org/W2162083125","https://openalex.org/W2009506202","https://openalex.org/W47559851","https://openalex.org/W2297694731","https://openalex.org/W204488290","https://openalex.org/W2071988253","https://openalex.org/W2096969571","https://openalex.org/W2040550925"],"abstract_inverted_index":{"Classifier":[0],"combination":[1],"is":[2,30,91,145,164],"an":[3,152],"effective":[4],"method":[5],"to":[6,19,136,160],"improve":[7],"the":[8,37,50,59,68,72,76,88,98,101,109,114,122,148,171],"recognition":[9,60,154],"accuracy":[10],"of":[11,39,62,95,124,142,170],"a":[12,118,162,167],"biometric":[13,22],"system.":[14],"It":[15],"has":[16],"been":[17],"applied":[18],"many":[20],"practical":[21,168],"systems":[23],"and":[24,52,66,121,129],"achieved":[25],"excellent":[26],"performance.":[27],"However,":[28],"there":[29],"little":[31],"literature":[32],"involving":[33],"theoretical":[34],"analysis":[35],"on":[36,84],"effectiveness":[38],"classifier":[40,74,116],"combination.":[41],"In":[42,55],"this":[43],"paper,":[44],"we":[45,57,105],"investigate":[46],"classifiers":[47,126],"combined":[48,64,73],"with":[49],"max":[51],"min":[53],"rules.":[54],"particular,":[56],"compute":[58],"performance":[61],"each":[63],"classifier,":[65],"illustrate":[67],"condition":[69],"in":[70],"which":[71,156],"outperforms":[75],"original":[77,115],"unimodal":[78],"classifier.":[79],"We":[80],"focus":[81],"our":[82,138],"study":[83],"personal":[85],"verification,":[86],"where":[87],"input":[89],"pattern":[90],"classified":[92],"into":[93],"one":[94],"two":[96],"categories,":[97],"genuine":[99],"or":[100],"impostor.":[102],"For":[103],"simplicity,":[104],"further":[106],"assume":[107],"that":[108],"matching":[110],"score":[111],"produced":[112],"by":[113],"follows":[117],"normal":[119],"distribution":[120],"outputs":[123],"different":[125],"are":[127,134],"independent":[128],"identically":[130],"distributed.":[131],"Randomly-generated":[132],"data":[133],"employed":[135],"test":[137],"conclusion.":[139],"The":[140],"influence":[141],"finite":[143],"samples":[144],"explored":[146],"at":[147],"same":[149],"time.":[150],"Moreover,":[151],"iris":[153],"system,":[155],"adopts":[157],"multiple":[158],"snapshots":[159],"identify":[161],"subject,":[163],"introduced":[165],"as":[166],"application":[169],"above":[172],"discussions.":[173]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
