{"id":"https://openalex.org/W2902763542","doi":"https://doi.org/10.1109/icpr.2018.8545659","title":"Generalized Fisher Discriminant Analysis as A Dimensionality Reduction Technique","display_name":"Generalized Fisher Discriminant Analysis as A Dimensionality Reduction Technique","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2902763542","doi":"https://doi.org/10.1109/icpr.2018.8545659","mag":"2902763542"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/107195/1/Jiang_Generalized_Fisher_Discriminant.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028322731","display_name":"Yuechi Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuechi Jiang","raw_affiliation_strings":["Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056524805","display_name":"F.H.F. Leung","orcid":"https://orcid.org/0000-0003-3921-7074"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Frank H. F. Leung","raw_affiliation_strings":["Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"994","last_page":"999"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9983000159263611,"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/T10860","display_name":"Speech and Audio Processing","score":0.9983000159263611,"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":0.9979000091552734,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.915459156036377},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.8706494569778442},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.7668548822402954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7247629761695862},{"id":"https://openalex.org/keywords/scatter-matrix","display_name":"Scatter matrix","score":0.6976406574249268},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6875792145729065},{"id":"https://openalex.org/keywords/multiple-discriminant-analysis","display_name":"Multiple discriminant analysis","score":0.6449528336524963},{"id":"https://openalex.org/keywords/optimal-discriminant-analysis","display_name":"Optimal discriminant analysis","score":0.6382445096969604},{"id":"https://openalex.org/keywords/fisher-kernel","display_name":"Fisher kernel","score":0.6271712779998779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6090006232261658},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5080130100250244},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5027284622192383},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.46739017963409424},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45903754234313965},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.42387813329696655},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3654076159000397},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2815367579460144},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.21727055311203003},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.08852094411849976},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0638304054737091}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.915459156036377},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.8706494569778442},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.7668548822402954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7247629761695862},{"id":"https://openalex.org/C176917957","wikidata":"https://www.wikidata.org/wiki/Q7430596","display_name":"Scatter matrix","level":4,"score":0.6976406574249268},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6875792145729065},{"id":"https://openalex.org/C58596280","wikidata":"https://www.wikidata.org/wiki/Q28324849","display_name":"Multiple discriminant analysis","level":3,"score":0.6449528336524963},{"id":"https://openalex.org/C104500394","wikidata":"https://www.wikidata.org/wiki/Q17104912","display_name":"Optimal discriminant analysis","level":3,"score":0.6382445096969604},{"id":"https://openalex.org/C207798031","wikidata":"https://www.wikidata.org/wiki/Q8563425","display_name":"Fisher kernel","level":5,"score":0.6271712779998779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6090006232261658},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5080130100250244},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5027284622192383},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.46739017963409424},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45903754234313965},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.42387813329696655},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3654076159000397},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2815367579460144},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.21727055311203003},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.08852094411849976},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0638304054737091},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2018.8545659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/107195","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/107195","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/107195/1/Jiang_Generalized_Fisher_Discriminant.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/107195","is_oa":true,"landing_page_url":"http://hdl.handle.net/10397/107195","pdf_url":"http://ira.lib.polyu.edu.hk/bitstream/10397/107195/1/Jiang_Generalized_Fisher_Discriminant.pdf","source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Paper"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2902763542.pdf","grobid_xml":"https://content.openalex.org/works/W2902763542.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1035843486","https://openalex.org/W1546503963","https://openalex.org/W1936725236","https://openalex.org/W1976700914","https://openalex.org/W1988115552","https://openalex.org/W2003231282","https://openalex.org/W2012531448","https://openalex.org/W2021012145","https://openalex.org/W2028780137","https://openalex.org/W2031245459","https://openalex.org/W2041657594","https://openalex.org/W2049993107","https://openalex.org/W2054419497","https://openalex.org/W2111149694","https://openalex.org/W2121647436","https://openalex.org/W2121812409","https://openalex.org/W2143304877","https://openalex.org/W2143340430","https://openalex.org/W2146047955","https://openalex.org/W2147147599","https://openalex.org/W2150796457","https://openalex.org/W2153635508","https://openalex.org/W2157785665","https://openalex.org/W2161939451","https://openalex.org/W2162698522","https://openalex.org/W2164071167","https://openalex.org/W2403026333","https://openalex.org/W2547467124","https://openalex.org/W2569831843","https://openalex.org/W2735139402","https://openalex.org/W2895787386","https://openalex.org/W2898034154","https://openalex.org/W4285719527","https://openalex.org/W4299345493","https://openalex.org/W6626913232","https://openalex.org/W6681521150","https://openalex.org/W6731620367"],"related_works":["https://openalex.org/W2141981133","https://openalex.org/W2365801610","https://openalex.org/W2354551251","https://openalex.org/W2386228546","https://openalex.org/W2235563642","https://openalex.org/W2354349698","https://openalex.org/W2150796457","https://openalex.org/W2086055175","https://openalex.org/W2388682444","https://openalex.org/W2162393942"],"abstract_inverted_index":{"Fisher":[0,67,104,110],"Discriminant":[1,68,95,100,105,111],"Analysis":[2,69,96,101,106,112,121],"(FDA)":[3],"has":[4],"been":[5,29],"widely":[6],"used":[7],"as":[8,83,85,92,131],"a":[9,73,152],"dimensionality":[10,132],"reduction":[11,133],"technique.":[12],"Its":[13],"application":[14],"varies":[15],"from":[16],"face":[17],"recognition":[18],"to":[19,42,118,140,155,170],"speaker":[20,136],"recognition.":[21],"In":[22,60],"the":[23,33,44,49,65,80,142,172,175,180],"past":[24],"two":[25,55],"decades,":[26],"there":[27],"have":[28],"many":[30,86],"variations":[31,38],"on":[32],"formulation":[34,75],"of":[35,89,126,144,147,159],"FDA.":[36,59,77,148],"Different":[37],"adopt":[39],"different":[40,87,145,157],"ways":[41],"combine":[43],"between-class":[45,176],"scatter":[46,51,177,182],"matrix":[47,178,183],"and":[48,108,179],"within-class":[50,181],"matrix,":[52],"which":[53,71],"are":[54,128],"basic":[56],"components":[57],"in":[58,138],"this":[61],"paper,":[62],"we":[63],"propose":[64],"Generalized":[66],"(GFDA),":[70],"provides":[72,151],"general":[74],"for":[76,135],"GFDA":[78,114,127,150],"generalizes":[79],"standard":[81],"FDA":[82,160],"well":[84],"variants":[88,146,158],"FDA,":[90],"such":[91],"Regularized":[93,98,109],"Linear":[94],"(R-LDA),":[97],"Kernel":[99],"(R-KDA),":[102],"Inverse":[103],"(IFDA),":[107],"(RFDA).":[113],"can":[115],"also":[116],"degenerate":[117],"Principal":[119],"Component":[120],"(PCA).":[122],"Four":[123],"special":[124],"types":[125],"then":[129],"applied":[130],"techniques":[134],"recognition,":[137],"order":[139],"investigate":[141],"performance":[143],"Basically,":[149],"convenient":[153],"way":[154],"compare":[156],"by":[161],"simply":[162],"changing":[163],"some":[164],"parameters.":[165],"It":[166],"makes":[167],"it":[168],"easier":[169],"explore":[171],"roles":[173],"that":[174],"play.":[184]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}