{"id":"https://openalex.org/W1996423054","doi":"https://doi.org/10.1145/2663204.2666270","title":"Neural Networks for Emotion Recognition in the Wild","display_name":"Neural Networks for Emotion Recognition in the Wild","publication_year":2014,"publication_date":"2014-11-12","ids":{"openalex":"https://openalex.org/W1996423054","doi":"https://doi.org/10.1145/2663204.2666270","mag":"1996423054"},"language":"en","primary_location":{"id":"doi:10.1145/2663204.2666270","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2663204.2666270","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Multimodal Interaction","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/A5040199138","display_name":"Micha\u0142 Grosicki","orcid":null},"institutions":[{"id":"https://openalex.org/I169109204","display_name":"Kielce University of Technology","ror":"https://ror.org/01zywja13","country_code":"PL","type":"education","lineage":["https://openalex.org/I169109204"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Micha\u0142 Grosicki","raw_affiliation_strings":["Kielce University of Technology, Kielce, Poland","[Kielce University of Technology, Kielce, Poland]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kielce University of Technology, Kielce, Poland","institution_ids":["https://openalex.org/I169109204"]},{"raw_affiliation_string":"[Kielce University of Technology, Kielce, Poland]","institution_ids":["https://openalex.org/I169109204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5040199138"],"corresponding_institution_ids":["https://openalex.org/I169109204"],"apc_list":null,"apc_paid":null,"fwci":0.3596,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56668353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"467","last_page":"472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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":0.9977999925613403,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.7833091020584106},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7200876474380493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6662531495094299},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6207603812217712},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5924513339996338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5518020391464233},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5449260473251343},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.49318188428878784},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.46990200877189636},{"id":"https://openalex.org/keywords/clips","display_name":"CLIPS","score":0.4674241244792938},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.4478932321071625},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41529154777526855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3732134699821472}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833091020584106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7200876474380493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6662531495094299},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6207603812217712},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5924513339996338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5518020391464233},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5449260473251343},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.49318188428878784},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.46990200877189636},{"id":"https://openalex.org/C2778739407","wikidata":"https://www.wikidata.org/wiki/Q165372","display_name":"CLIPS","level":2,"score":0.4674241244792938},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.4478932321071625},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41529154777526855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3732134699821472},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2663204.2666270","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2663204.2666270","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th International Conference on Multimodal Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1964920275","https://openalex.org/W1981918162","https://openalex.org/W1992227055","https://openalex.org/W2081835714","https://openalex.org/W2095705004","https://openalex.org/W2143612262","https://openalex.org/W2145094598","https://openalex.org/W2158419735","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2604272474","https://openalex.org/W2997574889"],"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":{"In":[0,75],"this":[1],"paper":[2],"we":[3],"present":[4],"neural":[5,32],"networks":[6],"based":[7],"method":[8,97],"for":[9,72,81],"emotion":[10],"recognition.":[11],"Proposed":[12],"model":[13,112],"was":[14,54],"developed":[15],"as":[16],"part":[17],"of":[18,29,68,100],"2014":[19],"Emotion":[20],"Recognition":[21],"in":[22,60],"the":[23,76,87,109],"Wild":[24],"Challenge.":[25],"It":[26],"is":[27,103],"composed":[28],"modality":[30],"specific":[31],"networks,":[33],"which":[34,59,102],"where":[35,84],"trained":[36,55],"separately":[37],"on":[38,56],"audio":[39],"and":[40],"video":[41,46],"data":[42],"extracted":[43],"from":[44,49],"short":[45],"clips":[47],"taken":[48],"various":[50,79],"movies.":[51],"Each":[52],"network":[53],"frame-level":[57],"data,":[58],"later":[61],"stages":[62],"were":[63],"aggregated":[64],"by":[65,108,114],"simple":[66],"averaging":[67],"predicted":[69],"class":[70],"distributions":[71],"each":[73],"clip.":[74],"next":[77],"stage":[78],"techniques":[80],"combining":[82],"modalities":[83],"investigated":[85],"with":[86,93],"best":[88,110],"being":[89],"support":[90],"vector":[91],"machine":[92],"RBF":[94],"kernel.":[95],"Our":[96],"achieved":[98],"accuracy":[99],"37.84%,":[101],"better":[104],"than":[105],"33.7%":[106],"obtained":[107],"baseline":[111],"provided":[113],"organisers.":[115]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}