{"id":"https://openalex.org/W2135188618","doi":"https://doi.org/10.1109/ijcnn.2005.1556182","title":"Spectral feature analysis","display_name":"Spectral feature analysis","publication_year":2006,"publication_date":"2006-01-05","ids":{"openalex":"https://openalex.org/W2135188618","doi":"https://doi.org/10.1109/ijcnn.2005.1556182","mag":"2135188618"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2005.1556182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556182","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","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/A5100417188","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0001-7059-4287"},"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":true,"raw_author_name":"Fei Wang","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and System Department of Automation, Tsinghua University, Beijing, China","Department of Automation, Tsinghua University, Beijing (China)"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and System Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing (China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075880303","display_name":"Jingdong Wang","orcid":"https://orcid.org/0000-0002-4888-4445"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jingdong Wang","raw_affiliation_strings":["Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China","Hong Kong University of Science & Technology"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Hong Kong University of Science & Technology","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065063835","display_name":"Changshui Zhang","orcid":"https://orcid.org/0000-0002-8088-367X"},"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":"Changshui Zhang","raw_affiliation_strings":["State Key Laboratory of Intelligent Technology and System Department of Automation, Tsinghua University, Beijing, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Intelligent Technology and System Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100417188"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.1058,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.86166971,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1971","last_page":"1976"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9977999925613403,"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":0.9977999925613403,"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/T10320","display_name":"Neural Networks and Applications","score":0.995199978351593,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.7888271808624268},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7819868326187134},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6934599876403809},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6706596612930298},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6563995480537415},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6552935838699341},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6251415610313416},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5451223254203796},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5189111828804016},{"id":"https://openalex.org/keywords/spectral-analysis","display_name":"Spectral analysis","score":0.509397566318512},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4519124925136566},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.4388091564178467},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.361875981092453},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32172340154647827},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.17002499103546143},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06680607795715332}],"concepts":[{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.7888271808624268},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7819868326187134},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6934599876403809},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6706596612930298},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6563995480537415},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6552935838699341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6251415610313416},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5451223254203796},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5189111828804016},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.509397566318512},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4519124925136566},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.4388091564178467},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.361875981092453},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32172340154647827},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.17002499103546143},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06680607795715332},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C32891209","wikidata":"https://www.wikidata.org/wiki/Q483666","display_name":"Spectroscopy","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2005.1556182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2005.1556182","pdf_url":null,"source":{"id":"https://openalex.org/S4363609022","display_name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","issn_l":null,"issn":null,"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":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W37713582","https://openalex.org/W191001584","https://openalex.org/W1560724230","https://openalex.org/W1578099820","https://openalex.org/W1981193610","https://openalex.org/W2103560185","https://openalex.org/W2120377775","https://openalex.org/W2121947440","https://openalex.org/W2135674549","https://openalex.org/W2139850885","https://openalex.org/W2140095548","https://openalex.org/W2153934661","https://openalex.org/W2157083019","https://openalex.org/W2158001550","https://openalex.org/W2158078575","https://openalex.org/W3144619878","https://openalex.org/W6601517701","https://openalex.org/W6634702315","https://openalex.org/W6677945368","https://openalex.org/W6680905637","https://openalex.org/W6683047094","https://openalex.org/W6683180201","https://openalex.org/W6683383647"],"related_works":["https://openalex.org/W2379488555","https://openalex.org/W2753886092","https://openalex.org/W2152632846","https://openalex.org/W1992961908","https://openalex.org/W2014683590","https://openalex.org/W2807624202","https://openalex.org/W3138125914","https://openalex.org/W2359742711","https://openalex.org/W2139392257","https://openalex.org/W4285789115"],"abstract_inverted_index":{"We":[0,48,66],"have":[1],"seen":[2],"a":[3,56],"surge":[4],"of":[5,78,99,115],"interest":[6],"in":[7,76],"spectral-based":[8],"methods":[9,12,24],"and":[10,16,41,80],"kernel-based":[11],"for":[13,58,63],"machine":[14],"learning":[15],"data":[17,59,100],"mining.":[18],"Despite":[19],"the":[20,72,96,113],"significant":[21],"research,":[22],"these":[23],"remain":[25],"only":[26,55],"loosely":[27],"related.":[28],"In":[29],"this":[30],"paper,":[31],"we":[32],"give":[33],"theoretically":[34],"an":[35],"explicit":[36],"relation":[37],"between":[38],"spectral":[39,51,73,83,89],"clustering":[40,52,74],"weighted":[42],"kernel":[43],"principal":[44],"component":[45],"analysis":[46,85],"(WKPCA).":[47],"show":[49,112],"that":[50],"is":[53],"not":[54],"method":[57],"clustering,":[60],"but":[61],"also":[62],"feature":[64,84],"extraction.":[65],"are":[67,109],"then":[68],"able":[69],"to":[70,111],"reinterpret":[71],"algorithm":[75],"terms":[77],"WKPCA":[79],"propose":[81],"our":[82,116],"(SFA)":[86],"method.":[87,117],"The":[88],"features":[90],"extracted":[91],"by":[92],"SFA":[93],"can":[94],"capture":[95],"distinguishing":[97],"information":[98],"from":[101],"different":[102],"classes":[103],"effectively.":[104],"Finally":[105],"some":[106],"experimental":[107],"results":[108],"presented":[110],"effectiveness":[114]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
