{"id":"https://openalex.org/W3185593275","doi":"https://doi.org/10.3390/s21144927","title":"Deep-Learning-Based Multimodal Emotion Classification for Music Videos","display_name":"Deep-Learning-Based Multimodal Emotion Classification for Music Videos","publication_year":2021,"publication_date":"2021-07-20","ids":{"openalex":"https://openalex.org/W3185593275","doi":"https://doi.org/10.3390/s21144927","mag":"3185593275","pmid":"https://pubmed.ncbi.nlm.nih.gov/34300666"},"language":"en","primary_location":{"id":"doi:10.3390/s21144927","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21144927","pdf_url":"https://www.mdpi.com/1424-8220/21/14/4927/pdf?version=1626932904","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/14/4927/pdf?version=1626932904","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064192572","display_name":"Yagya Raj Pandeya","orcid":"https://orcid.org/0000-0002-9842-8704"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yagya Raj Pandeya","raw_affiliation_strings":["Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea"],"raw_orcid":"https://orcid.org/0000-0002-9842-8704","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea","institution_ids":["https://openalex.org/I80611190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030180662","display_name":"Bhuwan Bhattarai","orcid":"https://orcid.org/0000-0001-7014-4868"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bhuwan Bhattarai","raw_affiliation_strings":["Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea"],"raw_orcid":"https://orcid.org/0000-0001-7014-4868","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea","institution_ids":["https://openalex.org/I80611190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044837622","display_name":"Joonwhoan Lee","orcid":"https://orcid.org/0000-0003-1854-9643"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Joonwhoan Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jeonbuk National University, Jeonju-City 54896, Korea","institution_ids":["https://openalex.org/I80611190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044837622"],"corresponding_institution_ids":["https://openalex.org/I80611190"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":9.1111,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.98654438,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"21","issue":"14","first_page":"4927","last_page":"4927"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9995999932289124,"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/T11309","display_name":"Music and Audio Processing","score":0.9995999932289124,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9991999864578247,"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/T10860","display_name":"Speech and Audio Processing","score":0.9980000257492065,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7421270608901978},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.605330228805542},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.53671795129776},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5213057398796082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5162320137023926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3373875021934509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421270608901978},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.605330228805542},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.53671795129776},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5213057398796082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5162320137023926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3373875021934509}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005149","descriptor_name":"Facial Expression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005149","descriptor_name":"Facial Expression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005149","descriptor_name":"Facial Expression","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21144927","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21144927","pdf_url":"https://www.mdpi.com/1424-8220/21/14/4927/pdf?version=1626932904","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34300666","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34300666","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:4d355946e34740e580c5aa6f4b7869b7","is_oa":true,"landing_page_url":"https://doaj.org/article/4d355946e34740e580c5aa6f4b7869b7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 14, p 4927 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/14/4927/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21144927","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 14; Pages: 4927","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8309938","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8309938","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21144927","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21144927","pdf_url":"https://www.mdpi.com/1424-8220/21/14/4927/pdf?version=1626932904","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G7112868416","display_name":null,"funder_award_id":"NRF-2021R1A2C2006895","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3185593275.pdf"},"referenced_works_count":94,"referenced_works":["https://openalex.org/W306648316","https://openalex.org/W324222877","https://openalex.org/W625810977","https://openalex.org/W1522734439","https://openalex.org/W1866281937","https://openalex.org/W1974788265","https://openalex.org/W1983507146","https://openalex.org/W1990906375","https://openalex.org/W1994477474","https://openalex.org/W2003238582","https://openalex.org/W2016053056","https://openalex.org/W2044807399","https://openalex.org/W2066064791","https://openalex.org/W2072691998","https://openalex.org/W2087407704","https://openalex.org/W2116001771","https://openalex.org/W2121407761","https://openalex.org/W2133999183","https://openalex.org/W2149628368","https://openalex.org/W2159017231","https://openalex.org/W2170120951","https://openalex.org/W2171848217","https://openalex.org/W2172221443","https://openalex.org/W2177696193","https://openalex.org/W2306853856","https://openalex.org/W2308045930","https://openalex.org/W2410495683","https://openalex.org/W2414264648","https://openalex.org/W2437181147","https://openalex.org/W2439669381","https://openalex.org/W2469054758","https://openalex.org/W2469800920","https://openalex.org/W2525837902","https://openalex.org/W2534100733","https://openalex.org/W2551403050","https://openalex.org/W2584561145","https://openalex.org/W2585658440","https://openalex.org/W2587610376","https://openalex.org/W2590454526","https://openalex.org/W2592535880","https://openalex.org/W2606199256","https://openalex.org/W2621062873","https://openalex.org/W2742456661","https://openalex.org/W2752782242","https://openalex.org/W2790898510","https://openalex.org/W2795014578","https://openalex.org/W2799041689","https://openalex.org/W2801154741","https://openalex.org/W2803193013","https://openalex.org/W2810371401","https://openalex.org/W2887068828","https://openalex.org/W2889134433","https://openalex.org/W2890805343","https://openalex.org/W2891191887","https://openalex.org/W2896082894","https://openalex.org/W2911289944","https://openalex.org/W2946198181","https://openalex.org/W2949191678","https://openalex.org/W2952047488","https://openalex.org/W2963155035","https://openalex.org/W2963162200","https://openalex.org/W2963420686","https://openalex.org/W2963452792","https://openalex.org/W2963524571","https://openalex.org/W2963609745","https://openalex.org/W2965507238","https://openalex.org/W2966094747","https://openalex.org/W2968635608","https://openalex.org/W2980581183","https://openalex.org/W2990503944","https://openalex.org/W3006417242","https://openalex.org/W3007589762","https://openalex.org/W3016970897","https://openalex.org/W3035570025","https://openalex.org/W3084086733","https://openalex.org/W3085812513","https://openalex.org/W3092379909","https://openalex.org/W3099153556","https://openalex.org/W3101237977","https://openalex.org/W3101923269","https://openalex.org/W3105198788","https://openalex.org/W3116444474","https://openalex.org/W3122111104","https://openalex.org/W4205952203","https://openalex.org/W4251591997","https://openalex.org/W4388317387","https://openalex.org/W6600375405","https://openalex.org/W6716267576","https://openalex.org/W6719864382","https://openalex.org/W6750843368","https://openalex.org/W6762979606","https://openalex.org/W6766730020","https://openalex.org/W6766969295","https://openalex.org/W6770046989"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3082059448","https://openalex.org/W4313640622","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694"],"abstract_inverted_index":{"Music":[0],"videos":[1],"contain":[2],"a":[3,15,30,83],"great":[4],"deal":[5],"of":[6,35,115,178,187],"visual":[7,103,168],"and":[8,25,52,68,76,102,131,134,149,160,167,180],"acoustic":[9,101],"information.":[10],"Each":[11],"information":[12,66,147],"source":[13],"within":[14],"music":[16,109],"video":[17],"influences":[18],"the":[19,23,64,73,78,112,124,184],"emotions":[20],"conveyed":[21],"through":[22],"audio":[24],"video,":[26,51,110],"suggesting":[27],"that":[28,47],"only":[29],"multimodal":[31,140,161],"approach":[32],"is":[33,119],"capable":[34],"achieving":[36],"efficient":[37],"affective":[38,44],"computing.":[39],"This":[40],"paper":[41],"presents":[42],"an":[43,176,181],"computing":[45],"system":[46],"relies":[48],"on":[49],"music,":[50],"facial":[53],"expression":[54],"cues,":[55],"making":[56],"it":[57],"useful":[58],"for":[59],"emotional":[60,104],"analysis.":[61],"We":[62,153],"applied":[63],"audio-video":[65],"exchange":[67],"boosting":[69,150],"methods":[70,137],"to":[71],"regularize":[72],"training":[74],"process":[75],"reduced":[77,121],"computational":[79,113],"costs":[80],"by":[81,122],"using":[82],"separable":[84],"convolution":[85,127],"strategy.":[86],"In":[87],"sum,":[88],"our":[89,155],"empirical":[90],"findings":[91,156],"are":[92,142],"as":[93],"follows:":[94],"(1)":[95],"Multimodal":[96],"representations":[97,141],"efficiently":[98],"capture":[99],"all":[100],"clues":[105],"included":[106],"in":[107,144],"each":[108,116],"(2)":[111],"cost":[114],"neural":[117],"network":[118],"significantly":[120],"factorizing":[123],"standard":[125],"2D/3D":[126],"into":[128,139],"separate":[129],"channels":[130],"spatiotemporal":[132],"interactions,":[133],"(3)":[135],"information-sharing":[136],"incorporated":[138],"helpful":[143],"guiding":[145],"individual":[146],"flow":[148],"overall":[151],"performance.":[152],"tested":[154],"across":[157],"several":[158],"unimodal":[159],"networks":[162],"against":[163],"various":[164],"evaluation":[165],"metrics":[166],"analyzers.":[169],"Our":[170],"best":[171],"classifier":[172],"attained":[173],"74%":[174],"accuracy,":[175],"f1-score":[177],"0.73,":[179],"area":[182],"under":[183],"curve":[185],"score":[186],"0.926.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}