{"id":"https://openalex.org/W4387973218","doi":"https://doi.org/10.1142/s0218126624501317","title":"Classroom Facial Expression Recognition Method Based on Conv3D-ConvLSTM-SEnet in Online Education Environment","display_name":"Classroom Facial Expression Recognition Method Based on Conv3D-ConvLSTM-SEnet in Online Education Environment","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4387973218","doi":"https://doi.org/10.1142/s0218126624501317"},"language":"en","primary_location":{"id":"doi:10.1142/s0218126624501317","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624501317","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-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/A5075871120","display_name":"Rong Fu","orcid":"https://orcid.org/0000-0002-8235-4130"},"institutions":[{"id":"https://openalex.org/I2802584641","display_name":"Leshan Normal University","ror":"https://ror.org/036cvz290","country_code":"CN","type":"education","lineage":["https://openalex.org/I2802584641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Fu","raw_affiliation_strings":["School of Educational Sciences, Leshan Normal University, Leshan, Sichuan 614000, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-8235-4130","affiliations":[{"raw_affiliation_string":"School of Educational Sciences, Leshan Normal University, Leshan, Sichuan 614000, P. R. China","institution_ids":["https://openalex.org/I2802584641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101564469","display_name":"M. Tian","orcid":"https://orcid.org/0009-0009-9002-5933"},"institutions":[{"id":"https://openalex.org/I2802584641","display_name":"Leshan Normal University","ror":"https://ror.org/036cvz290","country_code":"CN","type":"education","lineage":["https://openalex.org/I2802584641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mijuan Tian","raw_affiliation_strings":["School of Educational Sciences, Leshan Normal University, Leshan, Sichuan 614000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0009-9002-5933","affiliations":[{"raw_affiliation_string":"School of Educational Sciences, Leshan Normal University, Leshan, Sichuan 614000, P. R. China","institution_ids":["https://openalex.org/I2802584641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2802584641"],"apc_list":null,"apc_paid":null,"fwci":0.1586,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54441704,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"33","issue":"07","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12260","display_name":"Educational Technology and Pedagogy","score":0.6988000273704529,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12260","display_name":"Educational Technology and Pedagogy","score":0.6988000273704529,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12705","display_name":"Educational Reforms and Innovations","score":0.6518999934196472,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6628848910331726},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.6330523490905762},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6154363751411438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5638712048530579},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5313584804534912},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5192065834999084},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.42015600204467773},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.41211187839508057},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24291419982910156},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.20967158675193787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6628848910331726},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.6330523490905762},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6154363751411438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5638712048530579},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5313584804534912},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5192065834999084},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.42015600204467773},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.41211187839508057},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24291419982910156},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.20967158675193787},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218126624501317","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624501317","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2053432263","https://openalex.org/W2103943262","https://openalex.org/W2106115875","https://openalex.org/W2492893994","https://openalex.org/W2618530766","https://openalex.org/W2731811438","https://openalex.org/W2752782242","https://openalex.org/W2760212863","https://openalex.org/W2905054565","https://openalex.org/W2931011950","https://openalex.org/W2969522137","https://openalex.org/W2969985801","https://openalex.org/W2974596102","https://openalex.org/W2979579363","https://openalex.org/W2997678817","https://openalex.org/W3011425517","https://openalex.org/W3035565904","https://openalex.org/W3090132571","https://openalex.org/W3107569919","https://openalex.org/W3126625480","https://openalex.org/W3128764679","https://openalex.org/W3184571633","https://openalex.org/W3204340584","https://openalex.org/W4285505496","https://openalex.org/W4293198324","https://openalex.org/W4293731203","https://openalex.org/W4296849331","https://openalex.org/W4316672138","https://openalex.org/W4385638793"],"related_works":["https://openalex.org/W2392243736","https://openalex.org/W86652014","https://openalex.org/W2328518092","https://openalex.org/W3101249758","https://openalex.org/W2382079200","https://openalex.org/W2374091470","https://openalex.org/W1902660783","https://openalex.org/W3147584709","https://openalex.org/W3088721469","https://openalex.org/W4365802474"],"abstract_inverted_index":{"A":[0],"Facial":[1],"Expression":[2],"Recognition":[3],"(FER)":[4,28],"method":[5,127,156,189],"based":[6,51,95,212],"on":[7,52,96,183,193,213],"Conv3D-ConvLSTM-SEnet":[8],"in":[9,23,195,202],"an":[10],"online":[11,196],"education":[12],"environment":[13],"is":[14,32],"proposed":[15,107,124,155,188],"to":[16,34,70,88,178],"address":[17],"the":[18,36,44,54,59,72,81,110,129,141,154,158,179,184],"issue":[19],"of":[20,41,48,58,74,168],"low":[21],"accuracy":[22,120],"current":[24],"classroom":[25,121,125,197],"expression":[26],"recognition":[27],"methods.":[29],"Firstly,":[30],"ConvLSTM":[31,97],"used":[33],"integrate":[35],"local":[37],"feature":[38],"extraction":[39],"ability":[40,47],"CNN":[42],"and":[43,50,77,98,114,128,135,146,163,174,204],"temporal":[45],"modeling":[46],"LSTM,":[49],"this,":[53],"rich":[55],"spatial":[56],"features":[57,113],"image":[60],"are":[61,85],"characterized.":[62],"Then,":[63],"by":[64,108],"introducing":[65],"Depth":[66],"Separated":[67],"Convolution":[68],"(DSC)":[69],"change":[71],"number":[73],"output":[75,92],"channels":[76],"separate":[78],"each":[79],"channel,":[80],"Feature":[82],"Maps":[83],"(F-M)":[84],"sequentially":[86],"concatenated":[87],"obtain":[89],"a":[90,101],"multi-channel":[91],"F-M.":[93],"Finally,":[94],"SEnet":[99],"modules,":[100],"Conv3D":[102],"ConvLSTM-based":[103],"FER":[104,126,192],"model":[105],"was":[106],"redistributing":[109],"extracted":[111],"abstract":[112],"basic":[115],"texture":[116],"features,":[117],"achieving":[118],"high":[119],"FER.":[122],"The":[123,150,187],"other":[130,180],"five":[131,181],"methods":[132,182],"were":[133],"compared":[134,177],"analyzed":[136],"through":[137],"simulation":[138],"experiments":[139],"using":[140],"CK[Formula:":[142],"see":[143],"text],":[144],"FER2013":[145,185],"JAFFE":[147],"datasets,":[148],"respectively.":[149],"results":[151],"indicate":[152],"that":[153],"achieves":[157],"highest":[159],"accuracy,":[160],"precision,":[161],"recall,":[162],"F1":[164],"score,":[165],"with":[166],"improvements":[167],"at":[169],"least":[170],"1.85%,":[171],"2.41%,":[172],"1.18%":[173],"2.05%,":[175],"respectively,":[176],"dataset.":[186],"can":[190],"perform":[191],"students":[194],"teaching,":[198],"detect":[199],"their":[200],"emotions":[201],"real-time,":[203],"help":[205],"teachers":[206],"make":[207],"better":[208],"course":[209],"teaching":[210],"adjustments":[211],"this.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}