{"id":"https://openalex.org/W3180490915","doi":"https://doi.org/10.1186/s40537-021-00522-x","title":"Separable convolutional neural networks for facial expressions recognition","display_name":"Separable convolutional neural networks for facial expressions recognition","publication_year":2021,"publication_date":"2021-10-16","ids":{"openalex":"https://openalex.org/W3180490915","doi":"https://doi.org/10.1186/s40537-021-00522-x","mag":"3180490915"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-021-00522-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00522-x","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00522-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00522-x","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016075689","display_name":"Andry Chowanda","orcid":"https://orcid.org/0000-0002-2150-414X"},"institutions":[{"id":"https://openalex.org/I166073570","display_name":"Binus University","ror":"https://ror.org/03zmf4s77","country_code":"ID","type":"education","lineage":["https://openalex.org/I166073570"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Andry Chowanda","raw_affiliation_strings":["Computer Science Department, School of Computer Science, Bina Nusantara University, 11480, Jakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, School of Computer Science, Bina Nusantara University, 11480, Jakarta, Indonesia","institution_ids":["https://openalex.org/I166073570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5016075689"],"corresponding_institution_ids":["https://openalex.org/I166073570"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":2.9186,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.90638976,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9961000084877014,"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":0.8466548919677734},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.722118079662323},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6817149519920349},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5661605000495911},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5308676362037659},{"id":"https://openalex.org/keywords/creatures","display_name":"Creatures","score":0.4785783290863037},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46723586320877075},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4464885890483856},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4141031503677368},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.339835524559021},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32449352741241455}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8466548919677734},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.722118079662323},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6817149519920349},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5661605000495911},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5308676362037659},{"id":"https://openalex.org/C86792732","wikidata":"https://www.wikidata.org/wiki/Q1416338","display_name":"Creatures","level":3,"score":0.4785783290863037},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46723586320877075},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4464885890483856},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4141031503677368},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.339835524559021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32449352741241455},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"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/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-021-00522-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00522-x","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00522-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fa45ae581a834a1b8ff15f8af9c677f5","is_oa":true,"landing_page_url":"https://doaj.org/article/fa45ae581a834a1b8ff15f8af9c677f5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 8, Iss 1, Pp 1-17 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-021-00522-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-021-00522-x","pdf_url":"https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-021-00522-x","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3180490915.pdf","grobid_xml":"https://content.openalex.org/works/W3180490915.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W113801120","https://openalex.org/W1595126664","https://openalex.org/W1968015059","https://openalex.org/W2028542415","https://openalex.org/W2041616772","https://openalex.org/W2097128017","https://openalex.org/W2103943262","https://openalex.org/W2106115875","https://openalex.org/W2125186487","https://openalex.org/W2132555391","https://openalex.org/W2149875516","https://openalex.org/W2161634108","https://openalex.org/W2295107390","https://openalex.org/W2339343773","https://openalex.org/W2531199670","https://openalex.org/W2531409750","https://openalex.org/W2570163329","https://openalex.org/W2604209953","https://openalex.org/W2625929003","https://openalex.org/W2734336247","https://openalex.org/W2799041689","https://openalex.org/W2910415608","https://openalex.org/W2919597834","https://openalex.org/W2949833607","https://openalex.org/W2963112684","https://openalex.org/W2963712289","https://openalex.org/W2964347177","https://openalex.org/W2964350391","https://openalex.org/W2977279011","https://openalex.org/W2977483766","https://openalex.org/W2978010459","https://openalex.org/W2982039661","https://openalex.org/W3003850414","https://openalex.org/W3121847537","https://openalex.org/W3124054989","https://openalex.org/W3135267258","https://openalex.org/W3138357254","https://openalex.org/W3138598836","https://openalex.org/W3161346624","https://openalex.org/W4210812838","https://openalex.org/W4211153864","https://openalex.org/W4230277160","https://openalex.org/W6600116659","https://openalex.org/W6600258949"],"related_works":["https://openalex.org/W2309668926","https://openalex.org/W2112819298","https://openalex.org/W2393782702","https://openalex.org/W2312254833","https://openalex.org/W4231246704","https://openalex.org/W2299489928","https://openalex.org/W3174858995","https://openalex.org/W2484013627","https://openalex.org/W1531166605","https://openalex.org/W641005915"],"abstract_inverted_index":{"Abstract":[0],"Social":[1],"interactions":[2],"are":[3],"important":[4,14],"for":[5,70],"us,":[6],"humans,":[7],"as":[8,63],"social":[9,17],"creatures.":[10],"Emotions":[11],"play":[12],"an":[13,84],"part":[15],"in":[16],"interactions.":[18],"They":[19],"usually":[20],"express":[21],"meanings":[22],"along":[23],"with":[24,101,121],"the":[25,29,46,53,76,122,129,133,136,153,162],"spoken":[26],"utterances":[27],"to":[28,38,51,88,97,118,142],"interlocutors.":[30],"Automatic":[31],"facial":[32,59],"expressions":[33],"recognition":[34,57],"is":[35],"one":[36],"technique":[37],"automatically":[39],"capture,":[40],"recognise,":[41],"and":[42,90,111,146,149],"understand":[43],"emotions":[44,56,71],"from":[45,58],"interlocutor.":[47],"Many":[48],"techniques":[49],"proposed":[50,123,130],"increase":[52],"accuracy":[54,145,159],"of":[55,75,79],"cues.":[60],"Architecture":[61],"such":[62],"convolutional":[64,80],"neural":[65,81],"networks":[66,82,100],"demonstrates":[67],"promising":[68],"results":[69,126],"recognition.":[72,93],"However,":[73],"most":[74],"current":[77],"models":[78],"require":[83],"enormous":[85],"computational":[86],"power":[87],"train":[89],"process":[91],"emotional":[92],"This":[94],"research":[95],"aims":[96],"build":[98],"compact":[99,151],"depthwise":[102],"separable":[103],"layers":[104],"while":[105],"also":[106],"maintaining":[107],"performance.":[108],"Three":[109],"datasets":[110],"three":[112],"other":[113,137,154],"similar":[114],"architectures":[115],"were":[116],"used":[117],"be":[119],"compared":[120],"architecture.":[124],"The":[125,156],"show":[127],"that":[128],"architecture":[131,163],"performed":[132],"best":[134,157],"among":[135],"architectures.":[138,155],"It":[139],"achieved":[140,160],"up":[141],"13%":[143],"better":[144],"6\u201371%":[147],"smaller":[148],"more":[150],"than":[152],"testing":[158],"by":[161],"was":[164],"99.4%.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}