{"id":"https://openalex.org/W4412692182","doi":"https://doi.org/10.32604/cmc.2025.065061","title":"A YOLOv11-Based Deep Learning Framework for Multi-Class Human Action Recognition","display_name":"A YOLOv11-Based Deep Learning Framework for Multi-Class Human Action Recognition","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412692182","doi":"https://doi.org/10.32604/cmc.2025.065061"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.065061","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065061","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.065061","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119091666","display_name":"Nayeemul Islam Nayeem","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nayeemul Islam Nayeem","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006074547","display_name":"Shirin Mahbuba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shirin Mahbuba","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030434814","display_name":"S. Disha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanjida Islam Disha","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119091667","display_name":"Md Rifat Hossain Buiyan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md Rifat Hossain Buiyan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008671456","display_name":"Shakila Rahman","orcid":"https://orcid.org/0000-0001-6375-4174"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shakila Rahman","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009252576","display_name":"M. Abdullah\u2010Al\u2010Wadud","orcid":"https://orcid.org/0000-0001-6767-3574"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. Abdullah-Al-Wadud","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036848523","display_name":"Jia Uddin","orcid":"https://orcid.org/0000-0002-3403-4095"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia Uddin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5119091666"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4049,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83751471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"85","issue":"1","first_page":"1541","last_page":"1557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9621000289916992,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9621000289916992,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9401999711990356,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9297999739646912,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6785651445388794},{"id":"https://openalex.org/keywords/class-action","display_name":"Class action","score":0.6028502583503723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5614012479782104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.518990695476532},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5026354789733887},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.493269145488739},{"id":"https://openalex.org/keywords/action-learning","display_name":"Action learning","score":0.47691652178764343},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.24048739671707153},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.21204602718353271},{"id":"https://openalex.org/keywords/cooperative-learning","display_name":"Cooperative learning","score":0.11133050918579102},{"id":"https://openalex.org/keywords/teaching-method","display_name":"Teaching method","score":0.07808569073677063},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.05615580081939697}],"concepts":[{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6785651445388794},{"id":"https://openalex.org/C2776687834","wikidata":"https://www.wikidata.org/wiki/Q2783852","display_name":"Class action","level":3,"score":0.6028502583503723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5614012479782104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.518990695476532},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5026354789733887},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.493269145488739},{"id":"https://openalex.org/C183759332","wikidata":"https://www.wikidata.org/wiki/Q343680","display_name":"Action learning","level":4,"score":0.47691652178764343},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.24048739671707153},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.21204602718353271},{"id":"https://openalex.org/C51672120","wikidata":"https://www.wikidata.org/wiki/Q303446","display_name":"Cooperative learning","level":3,"score":0.11133050918579102},{"id":"https://openalex.org/C88610354","wikidata":"https://www.wikidata.org/wiki/Q1813494","display_name":"Teaching method","level":2,"score":0.07808569073677063},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.05615580081939697},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.065061","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065061","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.065061","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065061","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4000000059604645},{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2809793870","https://openalex.org/W2884256296","https://openalex.org/W2944017438","https://openalex.org/W2999723590","https://openalex.org/W3012546716","https://openalex.org/W3027736210","https://openalex.org/W4206103951","https://openalex.org/W4379184955","https://openalex.org/W4387496225","https://openalex.org/W4387790083","https://openalex.org/W4399017453"],"related_works":["https://openalex.org/W1494523486","https://openalex.org/W136506674","https://openalex.org/W2294250053","https://openalex.org/W2253550681","https://openalex.org/W39317772","https://openalex.org/W3122185720","https://openalex.org/W970202989","https://openalex.org/W2008243700","https://openalex.org/W2103249825","https://openalex.org/W1576128429"],"abstract_inverted_index":{"Human":[0],"activity":[1,37,56,66,168,236],"recognition":[2,330],"is":[3],"a":[4,135,140,215,252],"significant":[5],"area":[6],"of":[7,25,44,61,137,142,147,174,198,305,315],"research":[8,310],"in":[9,95,234,241,296],"artificial":[10],"intelligence":[11],"for":[12,34,53,120,131,166,176,179,182,186,191,284,328],"surveillance,":[13],"healthcare,":[14],"sports,":[15],"and":[16,74,82,100,109,128,139,151,153,158,164,184,188,224,248,282,302,318,325,332],"human-computer":[17],"interaction":[18],"applications.":[19],"The":[20,39,58,115,262],"article":[21,40],"benchmarks":[22,41],"the":[23,42,270,303,313],"performance":[24,43,132],"You":[26,45],"Only":[27,46],"Look":[28,47],"Once":[29,48],"version":[30,49],"11-based":[31,50],"(YOLOv11-based)":[32,51],"architecture":[33,52],"multi-class":[35,54],"human":[36,55],"recognition.":[38,57],"dataset":[59],"consists":[60],"14,186":[62],"images":[63,88],"across":[64],"19":[65],"classes,":[67],"from":[68,246],"dynamic":[69,242],"activities":[70,78,301],"such":[71,79,105,322],"as":[72,80,106,323],"running":[73],"swimming":[75],"to":[76,89,111,211,256,268,292,334],"static":[77,235,260],"sitting":[81],"sleeping.":[83],"Preprocessing":[84],"included":[85],"resizing":[86],"all":[87,167],"512":[90,91],"pixels,":[92],"annotating":[93],"them":[94],"YOLO\u2019s":[96],"bounding":[97],"box":[98],"format,":[99],"applying":[101],"data":[102,317],"augmentation":[103],"methods":[104,127],"flipping,":[107],"rotation,":[108],"cropping":[110],"enhance":[112],"model":[113,117],"generalization.":[114],"proposed":[116,266],"was":[118,189,231],"trained":[119],"100":[121],"epochs":[122],"with":[123,134,170,194],"adaptive":[124],"learning":[125],"rate":[126],"hyperparameter":[129],"optimization":[130],"improvement,":[133],"mAP@0.5":[136],"74.93%":[138],"mAP@0.5-0.95":[141],"64.11%,":[143],"outperforming":[144],"previous":[145],"versions":[146],"YOLO":[148],"(v10,":[149],"v9,":[150],"v8)":[152],"general-purpose":[154],"architectures":[155],"like":[156,214],"ResNet50":[157],"EfficientNet.":[159],"It":[160],"exhibited":[161],"improved":[162],"precision":[163,172],"recall":[165],"classes":[169],"high":[171],"values":[173],"0.76":[175],"running,":[177],"0.79":[178],"swimming,":[180],"0.80":[181],"sitting,":[183],"0.81":[185],"sleeping,":[187],"tested":[190],"real-time":[192],"deployment":[193],"an":[195,225,275],"inference":[196],"time":[197],"8.9":[199],"ms":[200],"per":[201],"image,":[202],"being":[203,251],"computationally":[204],"light.":[205],"Proposed":[206],"YOLOv11\u2019s":[207],"improvements":[208],"are":[209],"attributed":[210],"architectural":[212],"advancements":[213],"more":[216],"complex":[217],"feature":[218],"extraction":[219],"process,":[220],"better":[221],"attention":[222],"modules,":[223],"anchor-free":[226],"detection":[227],"mechanism.":[228],"While":[229],"YOLOv10":[230],"extremely":[232],"stable":[233],"recognition,":[237],"YOLOv9":[238],"performed":[239],"well":[240],"environments":[243],"but":[244],"suffered":[245],"overfitting,":[247],"YOLOv8,":[249],"while":[250],"decent":[253],"baseline,":[254],"failed":[255],"differentiate":[257],"between":[258,278],"overlapping":[259],"activities.":[261],"experimental":[263],"results":[264],"determine":[265],"YOLOv11":[267],"be":[269,293],"most":[271],"appropriate":[272],"model,":[273],"providing":[274],"ideal":[276],"balance":[277],"accuracy,":[279],"computational":[280],"efficiency,":[281],"robustness":[283],"real-world":[285,336],"deployment.":[286],"Nevertheless,":[287],"there":[288],"exist":[289],"certain":[290],"issues":[291],"addressed,":[294],"particularly":[295],"discriminating":[297],"against":[298],"visually":[299],"similar":[300],"use":[304],"publicly":[306],"available":[307],"datasets.":[308],"Future":[309],"will":[311],"entail":[312],"inclusion":[314],"3D":[316],"multimodal":[319],"sensor":[320],"inputs,":[321],"depth":[324],"motion":[326],"information,":[327],"enhancing":[329],"accuracy":[331],"generalizability":[333],"challenging":[335],"environments.":[337]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
