{"id":"https://openalex.org/W2549104515","doi":"https://doi.org/10.1109/ijcnn.2016.7727207","title":"Movie genre classification with Convolutional Neural Networks","display_name":"Movie genre classification with Convolutional Neural Networks","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2549104515","doi":"https://doi.org/10.1109/ijcnn.2016.7727207","mag":"2549104515"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727207","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":"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/A5103870192","display_name":"Gabriel S. Simoes","orcid":null},"institutions":[{"id":"https://openalex.org/I45643870","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Rio Grande do Sul","ror":"https://ror.org/025vmq686","country_code":"BR","type":"education","lineage":["https://openalex.org/I45643870"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Gabriel S. Simoes","raw_affiliation_strings":["Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil"],"affiliations":[{"raw_affiliation_string":"Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil","institution_ids":["https://openalex.org/I45643870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018120863","display_name":"J\u00f4natas Wehrmann","orcid":"https://orcid.org/0000-0001-9930-0908"},"institutions":[{"id":"https://openalex.org/I45643870","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Rio Grande do Sul","ror":"https://ror.org/025vmq686","country_code":"BR","type":"education","lineage":["https://openalex.org/I45643870"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jonatas Wehrmann","raw_affiliation_strings":["Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil"],"affiliations":[{"raw_affiliation_string":"Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil","institution_ids":["https://openalex.org/I45643870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039629929","display_name":"Rodrigo C. Barros","orcid":"https://orcid.org/0000-0002-0782-9482"},"institutions":[{"id":"https://openalex.org/I45643870","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Rio Grande do Sul","ror":"https://ror.org/025vmq686","country_code":"BR","type":"education","lineage":["https://openalex.org/I45643870"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rodrigo C. Barros","raw_affiliation_strings":["Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil"],"affiliations":[{"raw_affiliation_string":"Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil","institution_ids":["https://openalex.org/I45643870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019215692","display_name":"Duncan D. Ruiz","orcid":"https://orcid.org/0000-0002-4071-3246"},"institutions":[{"id":"https://openalex.org/I45643870","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica do Rio Grande do Sul","ror":"https://ror.org/025vmq686","country_code":"BR","type":"education","lineage":["https://openalex.org/I45643870"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Duncan D. Ruiz","raw_affiliation_strings":["Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil"],"affiliations":[{"raw_affiliation_string":"Pont\u00edffcia Universidade Cat\u00f3lica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil","institution_ids":["https://openalex.org/I45643870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103870192"],"corresponding_institution_ids":["https://openalex.org/I45643870"],"apc_list":null,"apc_paid":null,"fwci":3.3401,"has_fulltext":false,"cited_by_count":90,"citation_normalized_percentile":{"value":0.95156662,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"259","last_page":"266"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.998199999332428,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.998199999332428,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973999857902527,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9973000288009644,"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":0.8434329032897949},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7702852487564087},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6837388277053833},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6703413128852844},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5882439017295837},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5103339552879333},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5030760169029236},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4855043888092041},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4515017569065094},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4272860884666443},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3915867805480957},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38709962368011475}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8434329032897949},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7702852487564087},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837388277053833},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6703413128852844},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5882439017295837},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5103339552879333},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5030760169029236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4855043888092041},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4515017569065094},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4272860884666443},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3915867805480957},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38709962368011475},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727207","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W12796654","https://openalex.org/W28988658","https://openalex.org/W1566135517","https://openalex.org/W1686810756","https://openalex.org/W1963838563","https://openalex.org/W1980179845","https://openalex.org/W1983364832","https://openalex.org/W1999546964","https://openalex.org/W2015861736","https://openalex.org/W2016053056","https://openalex.org/W2016531398","https://openalex.org/W2022508996","https://openalex.org/W2047245698","https://openalex.org/W2067191022","https://openalex.org/W2076771430","https://openalex.org/W2088340225","https://openalex.org/W2090342772","https://openalex.org/W2097117768","https://openalex.org/W2107462874","https://openalex.org/W2112796928","https://openalex.org/W2125283600","https://openalex.org/W2148050970","https://openalex.org/W2150134853","https://openalex.org/W2154579312","https://openalex.org/W2159184562","https://openalex.org/W2162762921","https://openalex.org/W2163605009","https://openalex.org/W2165939745","https://openalex.org/W2167510172","https://openalex.org/W2212050411","https://openalex.org/W2919115771","https://openalex.org/W4236137412","https://openalex.org/W4240980853","https://openalex.org/W6600520985","https://openalex.org/W6637373629","https://openalex.org/W6683233156","https://openalex.org/W6684191040","https://openalex.org/W6684372118"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4360783045","https://openalex.org/W2963346891","https://openalex.org/W3176438653","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Automatic":[0],"pattern":[1],"recognition":[2],"from":[3,38],"videos":[4],"is":[5,85],"a":[6,83,86,117,144,150],"high-complexity":[7],"task,":[8],"and":[9,22,49,77,131,161,178],"well-established":[10],"Machine":[11],"Learning":[12],"algorithms":[13],"have":[14,115],"difficulties":[15],"in":[16,19,41,71,91,95,101],"handling":[17],"it":[18,134,164],"an":[20],"efficient":[21],"effective":[23],"fashion.":[24],"Convolutional":[25],"Neural":[26],"Networks":[27],"are":[28,53,60,111,129],"the":[29,67,72,102,138,190],"state-of-the-art":[30,166,192],"method":[31,147,187],"for":[32,137,170],"supervised":[33],"image":[34,39],"classification,":[35,158],"borrowing":[36],"concepts":[37],"processing":[40],"order":[42],"to":[43,98,153],"ensure":[44],"some":[45],"degree":[46],"of":[47,55,66,74,88,104],"scale":[48],"position":[50],"invariance.":[51],"They":[52],"capable":[54],"detecting":[56],"primary":[57],"features,":[58],"which":[59],"then":[61],"combined":[62],"by":[63],"subsequent":[64],"layers":[65],"CNN":[68,151],"architecture,":[69],"resulting":[70],"detection":[73],"higher-order":[75],"complex":[76],"relevant":[78],"novel":[79,118,145,186],"features.":[80],"Considering":[81],"that":[82,148,184],"video":[84],"set":[87],"ordered":[89],"images":[90],"time,":[92],"we":[93,114,132,142,162],"propose":[94],"this":[96],"paper":[97],"explore":[99],"CNNs":[100],"context":[103],"movie":[105,119,155,171],"trailers":[106,120,126],"genre":[107,157],"classification.":[108],"Our":[109],"contributions":[110],"twofold.":[112],"First,":[113],"developed":[116],"dataset":[121],"with":[122,165],"more":[123],"than":[124],"3500":[125],"whose":[127],"genres":[128],"known,":[130],"make":[133],"publicly":[135],"available":[136],"interested":[139],"reader.":[140],"Second,":[141],"detail":[143],"classification":[146,172],"encapsulates":[149],"architecture":[152],"perform":[154],"trailer":[156],"namely":[159],"CNN-MoTion,":[160],"compare":[163],"feature":[167,180],"extraction":[168],"techniques":[169],"such":[173],"as":[174],"Gist,":[175],"CENTRIST,":[176],"w-CENTRIST,":[177],"low-level":[179],"extraction.":[181],"Results":[182],"show":[183],"our":[185],"significantly":[188],"outperforms":[189],"current":[191],"approaches.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}