{"id":"https://openalex.org/W2102838264","doi":"https://doi.org/10.1109/icpr.2008.4761201","title":"Fuzzy maximum scatter discriminant analysis and its application to face recognition","display_name":"Fuzzy maximum scatter discriminant analysis and its application to face recognition","publication_year":2008,"publication_date":"2008-12-01","ids":{"openalex":"https://openalex.org/W2102838264","doi":"https://doi.org/10.1109/icpr.2008.4761201","mag":"2102838264"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2008.4761201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761201","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","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/A5100336337","display_name":"Jianguo Wang","orcid":"https://orcid.org/0000-0002-6282-0456"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]},{"id":"https://openalex.org/I154341788","display_name":"Tangshan College","ror":"https://ror.org/00rfn0469","country_code":"CN","type":"education","lineage":["https://openalex.org/I154341788"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianguo Wang","raw_affiliation_strings":["Network & Education Center, Tangshan Teacher''s College, Tangshan, China","School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Network & Education Center, Tangshan Teacher''s College, Tangshan, China","institution_ids":["https://openalex.org/I154341788"]},{"raw_affiliation_string":"School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074121246","display_name":"Wankou Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wankou Yang","raw_affiliation_strings":["School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063288559","display_name":"Jingyu Yang","orcid":"https://orcid.org/0000-0002-7521-7920"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Yang","raw_affiliation_strings":["School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Nanjing University of Science and Technology of PLA, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100336337"],"corresponding_institution_ids":["https://openalex.org/I154341788","https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.13383298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9965999722480774,"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":0.9965999722480774,"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/scatter-matrix","display_name":"Scatter matrix","score":0.8271013498306274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7436804175376892},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.7057431936264038},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6842458844184875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6391153335571289},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5955718159675598},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5523381233215332},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5516999363899231},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5349810123443604},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5144248604774475},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.508679211139679},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4784274697303772},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.47741997241973877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.439128577709198},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19852322340011597},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.17451989650726318},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.09736388921737671}],"concepts":[{"id":"https://openalex.org/C176917957","wikidata":"https://www.wikidata.org/wiki/Q7430596","display_name":"Scatter matrix","level":4,"score":0.8271013498306274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7436804175376892},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.7057431936264038},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6842458844184875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6391153335571289},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5955718159675598},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5523381233215332},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5516999363899231},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5349810123443604},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5144248604774475},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.508679211139679},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4784274697303772},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.47741997241973877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.439128577709198},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19852322340011597},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.17451989650726318},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.09736388921737671},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2008.4761201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761201","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.1209","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.1209","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://figment.cse.usf.edu/~sfefilat/data/papers/ThAT9.10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1974097586","https://openalex.org/W1985809919","https://openalex.org/W2012352340","https://openalex.org/W2040895929","https://openalex.org/W2088900896","https://openalex.org/W2111149694","https://openalex.org/W2121647436","https://openalex.org/W2124925761","https://openalex.org/W2371425310"],"related_works":["https://openalex.org/W2141981133","https://openalex.org/W1978302214","https://openalex.org/W1963649114","https://openalex.org/W3147024994","https://openalex.org/W2321869780","https://openalex.org/W2162393942","https://openalex.org/W2025089370","https://openalex.org/W2589829774","https://openalex.org/W1570195136","https://openalex.org/W2379730211"],"abstract_inverted_index":{"In":[0],"this":[1,96],"paper,":[2],"a":[3,68],"reformative":[4],"scatter":[5,17,36,71,103],"difference":[6,18,72],"discriminant":[7,24,48],"criterion":[8,25],"(SDDC)":[9],"with":[10],"fuzzy":[11,69,81],"set":[12],"theory":[13],"is":[14,26,76,85,98],"studied.":[15],"The":[16],"between":[19],"between-class":[20],"and":[21,95,112],"within-class":[22,35],"as":[23],"effective":[27,113],"to":[28,39,63,87,100,108,114],"overcome":[29],"the":[30,34,51,55,64,80,89,109,129,132],"singularity":[31],"problem":[32,43],"of":[33,58,60,92,131],"matrix":[37],"due":[38],"small":[40],"sample":[41,62],"size":[42],"occurred":[44],"in":[45,78],"classical":[46],"Fisher":[47],"analysis.":[49],"However,":[50],"conventional":[52,110],"SDDC":[53,111],"assumes":[54],"same":[56],"level":[57],"relevance":[59],"each":[61],"corresponding":[65,102],"class.":[66],"So,":[67],"maximum":[70],"analysis":[73],"(FMSDA)":[74],"algorithm":[75],"proposed,":[77],"which":[79,105],"k-nearest":[82],"neighbor":[83],"(FKNN)":[84],"implemented":[86],"achieve":[88],"distribution":[90],"information":[91,97],"original":[93],"samples,":[94],"utilized":[99],"redefine":[101],"matrices":[104],"are":[106],"different":[107],"extract":[115],"discriminative":[116],"features":[117],"from":[118],"overlapping":[119],"(outlier)":[120],"samples.":[121],"Experiments":[122],"conducted":[123],"on":[124],"FERET":[125],"face":[126],"databases":[127],"demonstrate":[128],"effectiveness":[130],"proposed":[133],"method.":[134]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}