{"id":"https://openalex.org/W2095411731","doi":"https://doi.org/10.1109/tnnls.2014.2350993","title":"Two-Stage Regularized Linear Discriminant Analysis for 2-D Data","display_name":"Two-Stage Regularized Linear Discriminant Analysis for 2-D Data","publication_year":2014,"publication_date":"2014-09-17","ids":{"openalex":"https://openalex.org/W2095411731","doi":"https://doi.org/10.1109/tnnls.2014.2350993","mag":"2095411731","pmid":"https://pubmed.ncbi.nlm.nih.gov/25204000"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2014.2350993","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"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/A5104080365","display_name":"Jianhua Zhao","orcid":"https://orcid.org/0000-0003-4028-8478"},"institutions":[{"id":"https://openalex.org/I49185572","display_name":"Yunnan University of Finance And Economics","ror":"https://ror.org/04rhev598","country_code":"CN","type":"funder","lineage":["https://openalex.org/I49185572"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Zhao","raw_affiliation_strings":["School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China;"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China;","institution_ids":["https://openalex.org/I49185572"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086332189","display_name":"\u041b\u0435\u0439 \u0428\u0438","orcid":"https://orcid.org/0000-0003-1203-9984"},"institutions":[{"id":"https://openalex.org/I49185572","display_name":"Yunnan University of Finance And Economics","ror":"https://ror.org/04rhev598","country_code":"CN","type":"funder","lineage":["https://openalex.org/I49185572"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Shi","raw_affiliation_strings":["School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China;"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China;","institution_ids":["https://openalex.org/I49185572"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103535575","display_name":"Zhu Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"funder","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ji Zhu","raw_affiliation_strings":["Department of Statistics University of Michigan Ann Arbor MI USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics University of Michigan Ann Arbor MI USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.242,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":24,"citation_normalized_percentile":{"value":0.8238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":92},"biblio":{"volume":"26","issue":"8","first_page":"1669","last_page":"1681"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9807,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9542,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8446971},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6230172},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6111959},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.56547236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.55930364},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5498283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5464772},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5454971},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.521811},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.44007093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40950373},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33976835},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.31045833},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23257577},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08269405},{"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/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2014.2350993","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25204000","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.73,"id":"https://metadata.un.org/sdg/10"}],"grants":[{"funder":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation","award_id":"DMS0748389"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"U1302267"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"11161053"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"11361071"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61403337"},{"funder":"https://openalex.org/F4320334924","funder_display_name":"Program for New Century Excellent Talents in University","award_id":null}],"datasets":[],"versions":[],"referenced_works_count":31,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1541521713","https://openalex.org/W1554944419","https://openalex.org/W1768730780","https://openalex.org/W1915008591","https://openalex.org/W1966701961","https://openalex.org/W2021014470","https://openalex.org/W2033302519","https://openalex.org/W2033419168","https://openalex.org/W2036043678","https://openalex.org/W2046649434","https://openalex.org/W2049701820","https://openalex.org/W2059887748","https://openalex.org/W2070110734","https://openalex.org/W2089322632","https://openalex.org/W2097366995","https://openalex.org/W2100310139","https://openalex.org/W2105055468","https://openalex.org/W2120886275","https://openalex.org/W2121647436","https://openalex.org/W2138550913","https://openalex.org/W2143340430","https://openalex.org/W2154560360","https://openalex.org/W2154624311","https://openalex.org/W2155423555","https://openalex.org/W2162985290","https://openalex.org/W2164728239","https://openalex.org/W2169073444","https://openalex.org/W2171033594","https://openalex.org/W4238240379","https://openalex.org/W438762167"],"related_works":["https://openalex.org/W3145966574","https://openalex.org/W2788610776","https://openalex.org/W2566759662","https://openalex.org/W2388048830","https://openalex.org/W2386228546","https://openalex.org/W2365801610","https://openalex.org/W2150796457","https://openalex.org/W2141981133","https://openalex.org/W2086055175","https://openalex.org/W2016459271"],"abstract_inverted_index":{"Fisher":[0,88],"linear":[1],"discriminant":[2,149],"analysis":[3],"(LDA)":[4],"involves":[5],"within-class":[6,31],"and":[7,40,72,82,106,168,183],"between-class":[8,43],"covariance":[9,100],"matrices.":[10],"For":[11],"2-D":[12,61,111,181],"data":[13,185],"such":[14],"as":[15],"images,":[16],"regularized":[17,26],"LDA":[18,22,66,96],"(RLDA)":[19],"can":[20],"improve":[21,46],"due":[23],"to":[24,36,126,159],"the":[25,29,38,41,69,73,76,87,95,104,128,132,138,142,147,152,156,171],"eigenvalues":[27],"of":[28,180],"estimated":[30,42,173],"matrix.":[32,44],"However,":[33],"it":[34],"fails":[35],"consider":[37],"eigenvectors":[39],"To":[45],"these":[47],"two":[48,172],"matrices":[49,174],"simultaneously,":[50],"we":[51,118],"propose":[52,119],"in":[53,68,75,110,131,151,162],"this":[54],"paper":[55],"a":[56,64,120,136,163,178],"new":[57],"two-stage":[58],"method":[59],"for":[60],"data,":[62],"namely":[63],"bidirectional":[65],"(BLDA)":[67],"first":[70,133,139],"stage":[71,140,158],"RLDA":[74,83,161],"second":[77,157],"stage,":[78],"where":[79],"both":[80],"BLDA":[81,93],"are":[84],"based":[85],"on":[86,177],"criterion":[89],"that":[90,102,117,188],"tackles":[91],"correlation.":[92],"performs":[94],"under":[97],"special":[98],"separable":[99],"constraints":[101],"incorporate":[103],"row":[105],"column":[107],"correlations":[108],"inherent":[109],"data.":[112,153],"The":[113],"main":[114],"novelty":[115],"is":[116],"simple":[121],"but":[122],"effective":[123],"statistical":[124],"test":[125],"determine":[127],"subspace":[129],"dimensionality":[130,143],"stage.":[134],"As":[135],"result,":[137],"reduces":[141],"substantially":[144],"while":[145],"keeping":[146],"significant":[148],"information":[150],"This":[154],"enables":[155],"perform":[160],"much":[164],"lower":[165],"dimensional":[166],"subspace,":[167],"thus":[169],"improves":[170],"simultaneously.":[175],"Experiments":[176],"number":[179],"synthetic":[182],"real-world":[184],"sets":[186],"show":[187],"BLDA+RLDA":[189],"outperforms":[190],"several":[191],"closely":[192],"related":[193],"competitors.":[194]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2095411731","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":8},{"year":2016,"cited_by_count":1}],"updated_date":"2025-04-28T00:41:00.298560","created_date":"2016-06-24"}