{"id":"https://openalex.org/W2921079524","doi":"https://doi.org/10.1109/istel.2018.8661140","title":"Canonical Correlation Analysis for Data Fusion in Multimodal Emotion Recognition","display_name":"Canonical Correlation Analysis for Data Fusion in Multimodal Emotion Recognition","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2921079524","doi":"https://doi.org/10.1109/istel.2018.8661140","mag":"2921079524"},"language":"en","primary_location":{"id":"doi:10.1109/istel.2018.8661140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istel.2018.8661140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Symposium on Telecommunications (IST)","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/A5011712422","display_name":"Shahla Nemati","orcid":"https://orcid.org/0000-0003-2906-5871"},"institutions":[{"id":"https://openalex.org/I127908078","display_name":"Shahrekord University","ror":"https://ror.org/051rngw70","country_code":"IR","type":"education","lineage":["https://openalex.org/I127908078"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Shahla Nemati","raw_affiliation_strings":["Department of Computer Engineering, Shahrekord University, Shahrekord, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Shahrekord University, Shahrekord, Iran","institution_ids":["https://openalex.org/I127908078"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011712422"],"corresponding_institution_ids":["https://openalex.org/I127908078"],"apc_list":null,"apc_paid":null,"fwci":1.434,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8331071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"676","last_page":"681"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9980999827384949,"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/T12496","display_name":"Color perception and design","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T10057","display_name":"Face and Expression Recognition","score":0.9779000282287598,"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/canonical-correlation","display_name":"Canonical correlation","score":0.8596605062484741},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.8360368013381958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7492812871932983},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7209831476211548},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6767271161079407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5849506855010986},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5701462030410767},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5486536622047424},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5439527034759521},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.47174179553985596},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4521900415420532},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4275748133659363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07689344882965088},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06447425484657288}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.8596605062484741},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.8360368013381958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7492812871932983},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7209831476211548},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6767271161079407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849506855010986},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5701462030410767},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5486536622047424},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5439527034759521},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.47174179553985596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4521900415420532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4275748133659363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07689344882965088},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06447425484657288},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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":1,"locations":[{"id":"doi:10.1109/istel.2018.8661140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/istel.2018.8661140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 9th International Symposium on Telecommunications (IST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7099999785423279,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W146470039","https://openalex.org/W1133916940","https://openalex.org/W1589554437","https://openalex.org/W1932844280","https://openalex.org/W1971609128","https://openalex.org/W2002055708","https://openalex.org/W2006407148","https://openalex.org/W2063875787","https://openalex.org/W2081031258","https://openalex.org/W2081689238","https://openalex.org/W2084046180","https://openalex.org/W2088879970","https://openalex.org/W2117645142","https://openalex.org/W2123260696","https://openalex.org/W2135622467","https://openalex.org/W2156503193","https://openalex.org/W2170120951","https://openalex.org/W2584561145","https://openalex.org/W2594612337","https://openalex.org/W2618843390","https://openalex.org/W2736344293","https://openalex.org/W2738686333","https://openalex.org/W2743708141","https://openalex.org/W2786411768","https://openalex.org/W2792962410","https://openalex.org/W2806102057","https://openalex.org/W2807825768","https://openalex.org/W3152231500","https://openalex.org/W4231779508","https://openalex.org/W4233906183","https://openalex.org/W6635364467"],"related_works":["https://openalex.org/W73545470","https://openalex.org/W4224266612","https://openalex.org/W2383394264","https://openalex.org/W4320153225","https://openalex.org/W4293261942","https://openalex.org/W3125968744","https://openalex.org/W203959209","https://openalex.org/W2110287964","https://openalex.org/W2167701463","https://openalex.org/W4307407935"],"abstract_inverted_index":{"Multimodal":[0],"emotion":[1,7,85],"recognition":[2],"systems":[3,18],"aim":[4],"at":[5],"classifying":[6],"data,":[8],"usually":[9],"from":[10,28],"different":[11,20,58],"natures,":[12],"into":[13],"discrete":[14],"affective":[15],"categories.":[16],"These":[17],"fuse":[19],"modalities":[21,59,82,91,143],"as":[22,81],"each":[23],"modality":[24],"classifies":[25],"the":[26,35,64,71,88,104,116,119,128,147,174,185],"data":[27,47,109],"its":[29],"own":[30],"viewpoint":[31],"and":[32,76,101,141,144],"can":[33],"compensate":[34],"limitations":[36],"of":[37,106,118,158],"others":[38],"when":[39],"combining":[40],"with":[41,99,149],"them.":[42],"Existing":[43],"approaches":[44],"for":[45,83],"multimodal":[46],"fusion":[48,110],"either":[49],"use":[50,105],"feature-level":[51,108,120,134,169,176],"or":[52],"decision-level":[53,154,186],"fusion.":[54,155,187],"The":[55,156],"former":[56],"needs":[57],"to":[60,114,139,163],"be":[61],"synchronized":[62,98],"while":[63],"latter":[65],"has":[66],"not":[67,97,171],"this":[68,102,160],"limitation.":[69],"In":[70,112],"current":[72,129],"study,":[73],"audio,":[74],"visual,":[75],"users'":[77,94,150],"comments":[78,95,151],"are":[79,92,96],"used":[80],"video":[84],"recognition.":[86],"Although":[87],"first":[89,132],"two":[90],"synchronized,":[93],"them":[100],"makes":[103],"pure":[107],"impossible.":[111],"order":[113],"exploit":[115],"benefits":[117],"approach,":[121],"a":[122,153,181],"hybrid":[123],"method":[124,162,177],"is":[125],"proposed":[126,161],"in":[127],"study":[130],"which":[131],"applies":[133],"canonical":[135],"correlation":[136],"analysis":[137],"(CCA)":[138],"audio":[140],"visual":[142],"then":[145],"combines":[146],"outputs":[148],"using":[152,168],"results":[157],"applying":[159],"DEAP":[164],"dataset":[165],"shows":[166],"that":[167],"CCA":[170],"only":[172],"outperforms":[173],"baseline":[175],"but":[178],"also":[179],"achieves":[180],"higher":[182],"performance":[183],"than":[184]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
