{"id":"https://openalex.org/W2556027894","doi":"https://doi.org/10.1109/ijcnn.2016.7727879","title":"Facial expression recognition using a pairwise feature selection and classification approach","display_name":"Facial expression recognition using a pairwise feature selection and classification approach","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2556027894","doi":"https://doi.org/10.1109/ijcnn.2016.7727879","mag":"2556027894"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018819867","display_name":"Marcelo J. Cossetin","orcid":null},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marcelo J. Cossetin","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, PR, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, PR, Brazil","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008799936","display_name":"J\u00falio C\u00e9sar Nievola","orcid":"https://orcid.org/0000-0002-2212-4499"},"institutions":[{"id":"https://openalex.org/I176838256","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1","ror":"https://ror.org/02x1vjk79","country_code":"BR","type":"education","lineage":["https://openalex.org/I176838256"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Julio C. Nievola","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, PR, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Inform\u00e1tica, Pontif\u00edcia Universidade Cat\u00f3lica do Paran\u00e1, Curitiba, PR, Brazil","institution_ids":["https://openalex.org/I176838256"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074262951","display_name":"Alessandro L. Koerich","orcid":"https://orcid.org/0000-0001-5879-7014"},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alessandro L. Koerich","raw_affiliation_strings":["Department of Software and IT Engineering, Ecole de Technologie Sup\u00e9rieure, Montr\u00e9al, QC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software and IT Engineering, Ecole de Technologie Sup\u00e9rieure, Montr\u00e9al, QC, Canada","institution_ids":["https://openalex.org/I9736820"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8116,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.93892643,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5149","last_page":"5155"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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":0.9987999796867371,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9351999759674072,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.9269058704376221},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8167135119438171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7770067453384399},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6831640005111694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6769930720329285},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6436299085617065},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5349520444869995},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5246348977088928},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5165826082229614},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49024444818496704},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46106964349746704},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.44201380014419556},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4327229857444763},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42158228158950806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3407045304775238},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2815935015678406}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.9269058704376221},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8167135119438171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7770067453384399},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6831640005111694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6769930720329285},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6436299085617065},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5349520444869995},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5246348977088928},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5165826082229614},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49024444818496704},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46106964349746704},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.44201380014419556},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4327229857444763},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42158228158950806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3407045304775238},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2815935015678406},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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.2016.7727879","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727879","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1619385794","https://openalex.org/W1975866270","https://openalex.org/W1979753563","https://openalex.org/W1985874825","https://openalex.org/W2003238582","https://openalex.org/W2007341930","https://openalex.org/W2014696193","https://openalex.org/W2021890937","https://openalex.org/W2029005662","https://openalex.org/W2037712846","https://openalex.org/W2050508159","https://openalex.org/W2060230335","https://openalex.org/W2066332159","https://openalex.org/W2066628189","https://openalex.org/W2068920342","https://openalex.org/W2082692487","https://openalex.org/W2097461747","https://openalex.org/W2131150047","https://openalex.org/W2161362162","https://openalex.org/W2164598857","https://openalex.org/W2168562143","https://openalex.org/W2185975875","https://openalex.org/W2255794050","https://openalex.org/W2534272595","https://openalex.org/W3034751874","https://openalex.org/W3144058330","https://openalex.org/W6636627054","https://openalex.org/W6653896920","https://openalex.org/W6686536019","https://openalex.org/W6778907217"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241","https://openalex.org/W2354420595"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,75,114,124,149],"novel":[4],"approach":[5,22,67,189,205],"that":[6,68],"combines":[7],"specialized":[8],"pairwise":[9,66,100,107,138,144,188],"classifiers":[10,101,145],"trained":[11,104],"with":[12,105],"different":[13,195],"feature":[14,77,108],"subsets":[15],"for":[16],"facial":[17,157,196],"expression":[18],"classification.":[19],"The":[20,52,140],"proposed":[21,204],"first":[23],"detects":[24],"and":[25,40,74,87,171,173,181,198],"extracts":[26],"automatically":[27],"faces":[28],"from":[29,45,55,122],"images.":[30],"Next,":[31],"the":[32,62,85,111,128,156,174,187,199,203],"face":[33,116],"is":[34,80,134,146,190],"split":[35],"into":[36],"several":[37,210],"regular":[38],"zones":[39,57],"textural":[41],"features":[42,53,91,119,133],"are":[43,58,102,120,206],"extracted":[44,54,121],"each":[46,137],"zone":[47],"to":[48,60,82,88,92,136,153,192],"capture":[49],"local":[50],"information.":[51],"all":[56,70,118,143],"concatenated":[59],"model":[61],"whole":[63],"face.":[64],"A":[65],"considers":[69],"pairs":[71,96],"of":[72,97,132,142,178],"classes":[73],"hybrid":[76],"selection":[78],"strategy":[79],"used":[81],"both":[83],"reduce":[84],"dimensionality":[86],"select":[89],"relevant":[90],"discriminate":[93,193],"between":[94,194],"specific":[95],"classes.":[98],"Several":[99],"then":[103],"such":[106,123],"subsets.":[109],"At":[110],"end,":[112],"given":[113],"new":[115],"image,":[117],"face,":[125],"but":[126],"only":[127],"previously":[129],"selected":[130],"subset":[131],"inputted":[135],"classifier.":[139],"output":[141],"combined":[147],"using":[148],"majority":[150],"voting":[151],"rule":[152],"decide":[154],"on":[155,164],"expression.":[158],"Experiments":[159],"have":[160],"been":[161],"carried":[162],"out":[163],"three":[165],"publicly":[166],"available":[167],"datasets":[168],"(JAFFE,":[169],"CK":[170],"TFEID)":[172],"correct":[175],"classification":[176],"rates":[177],"99.05%,":[179],"98.07%":[180],"99.63%":[182],"were":[183],"achieved":[184,201],"respectively.":[185],"Therefore,":[186],"effective":[191],"expressions":[197],"results":[200],"by":[202],"slightly":[207],"better":[208],"than":[209],"current":[211],"approaches.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}