{"id":"https://openalex.org/W2756219612","doi":"https://doi.org/10.1145/3136755.3143015","title":"Emotion recognition in the wild using deep neural networks and Bayesian classifiers","display_name":"Emotion recognition in the wild using deep neural networks and Bayesian classifiers","publication_year":2017,"publication_date":"2017-11-03","ids":{"openalex":"https://openalex.org/W2756219612","doi":"https://doi.org/10.1145/3136755.3143015","mag":"2756219612"},"language":"en","primary_location":{"id":"doi:10.1145/3136755.3143015","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3136755.3143015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM International Conference on Multimodal Interaction","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1709.03820","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035960493","display_name":"Luca Surace","orcid":null},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Luca Surace","raw_affiliation_strings":["University of Calabria, Italy","University of Calabria,  Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria, Italy","institution_ids":["https://openalex.org/I45204951"]},{"raw_affiliation_string":"University of Calabria,  Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088288633","display_name":"Massimiliano Patacchiola","orcid":"https://orcid.org/0000-0002-9500-6899"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Massimiliano Patacchiola","raw_affiliation_strings":["Plymouth University, UK","Plymouth Univ., UK"],"affiliations":[{"raw_affiliation_string":"Plymouth University, UK","institution_ids":["https://openalex.org/I897542642"]},{"raw_affiliation_string":"Plymouth Univ., UK","institution_ids":["https://openalex.org/I897542642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001206166","display_name":"Elena Battini S\u00f6nmez","orcid":"https://orcid.org/0000-0003-0090-984X"},"institutions":[{"id":"https://openalex.org/I118036225","display_name":"Istanbul Bilgi University","ror":"https://ror.org/04pm4x478","country_code":"TR","type":"education","lineage":["https://openalex.org/I118036225"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Elena Battini S\u00f6nmez","raw_affiliation_strings":["Instanbul Bilgi University, Turkey"],"affiliations":[{"raw_affiliation_string":"Instanbul Bilgi University, Turkey","institution_ids":["https://openalex.org/I118036225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077855107","display_name":"William Spataro","orcid":"https://orcid.org/0000-0001-5776-9572"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"William Spataro","raw_affiliation_strings":["University of Calabria, Italy","University of Calabria,  Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria, Italy","institution_ids":["https://openalex.org/I45204951"]},{"raw_affiliation_string":"University of Calabria,  Italy","institution_ids":["https://openalex.org/I45204951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091768977","display_name":"Angelo Cangelosi","orcid":"https://orcid.org/0000-0002-4709-2243"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Angelo Cangelosi","raw_affiliation_strings":["Plymouth University, UK","Plymouth Univ., UK"],"affiliations":[{"raw_affiliation_string":"Plymouth University, UK","institution_ids":["https://openalex.org/I897542642"]},{"raw_affiliation_string":"Plymouth Univ., UK","institution_ids":["https://openalex.org/I897542642"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035960493"],"corresponding_institution_ids":["https://openalex.org/I45204951"],"apc_list":null,"apc_paid":null,"fwci":0.2343,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64936506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"593","last_page":"597"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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/T10057","display_name":"Face and Expression Recognition","score":0.9986000061035156,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7971840500831604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6644144058227539},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6452072262763977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6145261526107788},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5755311250686646},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.552661120891571},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5231229662895203},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5088801383972168},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.4950351119041443},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48195764422416687},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.46103692054748535},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4327140748500824},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42677390575408936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4120280146598816},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.16882604360580444}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7971840500831604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6644144058227539},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6452072262763977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6145261526107788},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5755311250686646},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.552661120891571},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5231229662895203},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5088801383972168},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.4950351119041443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48195764422416687},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.46103692054748535},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4327140748500824},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42677390575408936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4120280146598816},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.16882604360580444},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1145/3136755.3143015","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3136755.3143015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM International Conference on Multimodal Interaction","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.03820","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.03820","pdf_url":"https://arxiv.org/pdf/1709.03820","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2756219612","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1709.03820.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/a7881244-c735-4a78-96ff-1e0f0265a105","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/a7881244-c735-4a78-96ff-1e0f0265a105","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Surace, L, Patacchiola, M, S\u00f6nmez, E B, Spataro, W & Cangelosi, A 2017, Emotion recognition in the wild using deep neural networks and Bayesian classifiers. in ICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction. vol. 2017-January, Association for Computing Machinery, pp. 593-597, 19th ACM International Conference on Multimodal Interaction, ICMI 2017, Glasgow, United Kingdom, 13/11/17. https://doi.org/10.1145/3136755.3143015","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/a7881244-c735-4a78-96ff-1e0f0265a105","is_oa":false,"landing_page_url":"https://www.research.manchester.ac.uk/portal/en/publications/emotion-recognition-in-the-wild-using-deep-neural-networks-and-bayesian-classifiers(a7881244-c735-4a78-96ff-1e0f0265a105).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Surace, L, Patacchiola, M, S\u00f6nmez, E B, Spataro, W & Cangelosi, A 2017, Emotion recognition in the wild using deep neural networks and Bayesian classifiers. in ICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction. vol. 2017-January, Association for Computing Machinery, pp. 593-597, 19th ACM International Conference on Multimodal Interaction, ICMI 2017, Glasgow, United Kingdom, 13/11/17. https://doi.org/10.1145/3136755.3143015","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"doi:10.48550/arxiv.1709.03820","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.03820","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.03820","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.03820","pdf_url":"https://arxiv.org/pdf/1709.03820","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2756219612.pdf","grobid_xml":"https://content.openalex.org/works/W2756219612.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1519333772","https://openalex.org/W1522301498","https://openalex.org/W1596728080","https://openalex.org/W1603712378","https://openalex.org/W1651753422","https://openalex.org/W1817561967","https://openalex.org/W1981918162","https://openalex.org/W1986803802","https://openalex.org/W2032254851","https://openalex.org/W2047967129","https://openalex.org/W2050527683","https://openalex.org/W2068375500","https://openalex.org/W2094637479","https://openalex.org/W2095705004","https://openalex.org/W2103943262","https://openalex.org/W2113855951","https://openalex.org/W2135964285","https://openalex.org/W2146502635","https://openalex.org/W2158705122","https://openalex.org/W2159033850","https://openalex.org/W2159080219","https://openalex.org/W2160815625","https://openalex.org/W2170948832","https://openalex.org/W2211582303","https://openalex.org/W2253728219","https://openalex.org/W2273818082","https://openalex.org/W2506506742","https://openalex.org/W2546815862","https://openalex.org/W2547683630","https://openalex.org/W2587712052","https://openalex.org/W2595337020","https://openalex.org/W2621061298","https://openalex.org/W2767348466","https://openalex.org/W2912934387"],"related_works":["https://openalex.org/W2964290400","https://openalex.org/W2251198138","https://openalex.org/W2277498883","https://openalex.org/W2281407413","https://openalex.org/W3094335887","https://openalex.org/W2949973861","https://openalex.org/W2610961739","https://openalex.org/W2624018370","https://openalex.org/W2895443688","https://openalex.org/W3105990636","https://openalex.org/W2767618761","https://openalex.org/W2799075631","https://openalex.org/W2942994697","https://openalex.org/W3177157049","https://openalex.org/W3126856755","https://openalex.org/W2762208110","https://openalex.org/W2972819746","https://openalex.org/W2162753443","https://openalex.org/W2295001676","https://openalex.org/W3045352664"],"abstract_inverted_index":{"Group":[0],"emotion":[1,77],"recognition":[2],"in":[3,15,104],"the":[4,12,24,90,94,97,101,105,117,122],"wild":[5],"is":[6],"a":[7,43,47,62,75,83],"challenging":[8],"problem,":[9],"due":[10],"to":[11,88],"unstructured":[13],"environments":[14],"which":[16],"everyday":[17],"life":[18],"pictures":[19],"are":[20,30],"taken.":[21],"Some":[22],"of":[23,50,114],"obstacles":[25],"for":[26,100],"an":[27,112],"effective":[28],"classification":[29],"occlusions,":[31],"variable":[32],"lighting":[33],"conditions,":[34],"and":[35,54],"image":[36],"quality.":[37],"In":[38,86],"this":[39],"work":[40],"we":[41,92],"present":[42],"solution":[44],"based":[45],"on":[46,61,96,116],"novel":[48],"combination":[49],"deep":[51],"neural":[52,58],"networks":[53],"Bayesian":[55,72],"classifiers.":[56],"The":[57,71],"network":[59],"works":[60],"bottom-up":[63],"approach,":[64],"analyzing":[65],"emotions":[66],"expressed":[67],"by":[68],"isolated":[69],"faces.":[70],"classifier":[73],"estimates":[74],"global":[76],"integrating":[78],"top-down":[79],"features":[80],"obtained":[81],"through":[82],"scene":[84],"descriptor.":[85],"order":[87],"validate":[89],"system":[91],"tested":[93],"framework":[95],"dataset":[98],"released":[99],"Emotion":[102],"Recognition":[103],"Wild":[106],"Challenge":[107],"2017.":[108],"Our":[109],"method":[110],"achieved":[111],"accuracy":[113],"64.68%":[115],"test":[118],"set,":[119],"significantly":[120],"outperforming":[121],"53.62%":[123],"competition":[124],"baseline.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}