{"id":"https://openalex.org/W4402352491","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651244","title":"Classroom Behavior Recognition Model for Elementary and Middle School Students Based on Improved YOLOPose and Feature Fusion","display_name":"Classroom Behavior Recognition Model for Elementary and Middle School Students Based on Improved YOLOPose and Feature Fusion","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352491","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651244"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651244","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5024375176","display_name":"Zhuang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Wang","raw_affiliation_strings":["Southwest University,College of Computer & Information Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer & Information Science,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063427973","display_name":"Zhurong Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhurong Zhou","raw_affiliation_strings":["Southwest University,College of Computer & Information Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer & Information Science,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092025877","display_name":"Yi Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Chen","raw_affiliation_strings":["Southwest University,College of Computer & Information Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer & Information Science,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015782253","display_name":"Tianci Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianci Zheng","raw_affiliation_strings":["Southwest University,College of Computer & Information Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer & Information Science,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111319840","display_name":"Youlin He","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youlin He","raw_affiliation_strings":["Southwest University,College of Computer & Information Science,Chongqing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer & Information Science,Chongqing,China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":1.0772,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73052021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9660999774932861,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9660999774932861,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12222","display_name":"IoT-based Smart Home Systems","score":0.930899977684021,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13565","display_name":"Education and Learning Interventions","score":0.9175999760627747,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/feature","display_name":"Feature (linguistics)","score":0.6897988319396973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5693167448043823},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.5510532855987549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41979265213012695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38236913084983826},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.28155916929244995},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.06315445899963379}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6897988319396973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5693167448043823},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.5510532855987549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41979265213012695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38236913084983826},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.28155916929244995},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.06315445899963379},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651244","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4300000071525574,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1946084000","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2756368381","https://openalex.org/W2768380900","https://openalex.org/W2775376210","https://openalex.org/W2889985731","https://openalex.org/W2952122856","https://openalex.org/W2963263347","https://openalex.org/W3004524477","https://openalex.org/W3099319035","https://openalex.org/W3135848955","https://openalex.org/W3181162804","https://openalex.org/W3183430956","https://openalex.org/W3191120830","https://openalex.org/W3194790201","https://openalex.org/W3202672969","https://openalex.org/W3206715694","https://openalex.org/W4280638556","https://openalex.org/W4292787291","https://openalex.org/W4293248949","https://openalex.org/W4312308697","https://openalex.org/W4312360201","https://openalex.org/W4313854671","https://openalex.org/W4318255578","https://openalex.org/W4385346076","https://openalex.org/W4386076325","https://openalex.org/W6726497184","https://openalex.org/W6849535052"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W4386159726"],"abstract_inverted_index":{"Classroom":[0,99,144,199,212],"behavior":[1],"recognition":[2,14],"plays":[3],"a":[4,98,142,159],"key":[5],"role":[6],"in":[7,36,87,93,259],"the":[8,32,37,49,66,74,82,115,128,182,192,198,209,223,226,239,247,256,261,273,278,290,298,317],"process":[9],"of":[10,17,34,48,65,84,118,132,150,184,225,238,246],"educational":[11],"evaluation.":[12],"Automatic":[13],"and":[15,39,63,80,109,120,153,157,168,180,196,242,244,263,270,277,280,287,311],"analysis":[16],"students\u2019":[18],"classroom":[19,38,61],"behaviors":[20],"using":[21],"computer":[22],"vision":[23],"methods":[24,69],"are":[25,57,233],"important":[26],"for":[27,60,103,235,272,289],"teachers":[28],"to":[29,43,126,176,221,316],"better":[30],"observe":[31],"status":[33],"students":[35],"implement":[40],"appropriate":[41],"measures":[42],"help":[44],"students.":[45],"However,":[46],"most":[47,64],"object":[50,274],"detection":[51,275],"or":[52],"human":[53],"pose":[54],"estimation":[55],"models":[56],"not":[58,71],"optimized":[59],"scenarios,":[62],"feature":[67,129,136],"fusion":[68,179],"do":[70],"fully":[72],"explore":[73],"potential":[75],"connection":[76],"between":[77],"Multi-modal":[78],"information":[79],"consider":[81],"importance":[83,183],"local":[85,186],"features":[86],"appearance.":[88],"To":[89],"address":[90],"these":[91],"issues,":[92],"this":[94],"paper,":[95],"we":[96,113,140,190],"propose":[97],"Behavior":[100,145,213],"Recognition":[101,214],"Model":[102,147],"Students":[104],"based":[105,163,320],"on":[106,164,255,297,321],"Improved":[107,227,240,251],"YOLOPose":[108,119,133,241,252],"Feature":[110,160,172],"Fusion.":[111],"First,":[112],"improved":[114,267,284,301],"loss":[116],"function":[117],"used":[121,191,220,234],"Large":[122],"Kernel":[123],"Attention":[124,166],"Module":[125,162,174],"improve":[127,222],"extraction":[130],"ability":[131],"at":[134],"different":[135],"levels.":[137],"After":[138],"that,":[139],"built":[141],"Student":[143,211],"Classification":[146],"with":[148],"inputs":[149],"appearance":[151,185],"image":[152,155],"skeleton":[154],"(SCBC-PFAF),":[156],"proposed":[158],"Correction":[161],"Hybrid":[165],"(HAFCM)":[167],"an":[169],"Appearance":[170],"Local":[171],"Enhancement":[173],"(ALFEM)":[175],"achieve":[177],"early":[178],"learn":[181],"features.":[187],"For":[188],"datasets,":[189],"COCO":[193,217,257],"public":[194],"dataset":[195,218,300],"self-built":[197,231],"Panoramic":[200],"Human":[201],"Pose":[202],"Estimation":[203],"Dataset":[204],"(PoseClass)":[205],"as":[206,208],"well":[207],"Individual":[210],"Dataset(Bhv-Class).":[215],"The":[216,229,250,293],"was":[219,253],"pre-training":[224],"YOLOPose.":[228],"two":[230],"datasets":[232],"transfer":[236],"learning":[237],"training":[243],"testing":[245],"SCBC-PFAF,":[248],"respectively.":[249],"evaluated":[254,296],"dataset,":[258],"which":[260],"AP50":[262,279],"AP95":[264,281],"metrics":[265,282],"were":[266,283],"by":[268,285,303,306,309,313],"2.2%":[269],"4.9%":[271],"benchmark,":[276],"2.7%":[286],"3.6%":[288],"keypoint":[291],"benchmark.":[292],"constructed":[294],"SCBC-PFAF":[295],"Bhv-Class":[299],"accuracy":[302],"2%,":[304],"precision":[305],"0.7%,":[307],"recall":[308],"1.7%,":[310],"F1-Score":[312],"1.6%":[314],"relative":[315],"classification":[318],"model":[319],"late":[322],"fusion.":[323]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}