{"id":"https://openalex.org/W3196724361","doi":"https://doi.org/10.1155/2021/1016574","title":"Key Frame Extraction for Sports Training Based on Improved Deep Learning","display_name":"Key Frame Extraction for Sports Training Based on Improved Deep Learning","publication_year":2021,"publication_date":"2021-09-01","ids":{"openalex":"https://openalex.org/W3196724361","doi":"https://doi.org/10.1155/2021/1016574","mag":"3196724361"},"language":"en","primary_location":{"id":"doi:10.1155/2021/1016574","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/1016574","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/1016574.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/sp/2021/1016574.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001114182","display_name":"Changhai Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhai Lv","raw_affiliation_strings":["Ministry of Sports, Shandong Technology and Business University, Yantai 264005, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Sports, Shandong Technology and Business University, Yantai 264005, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101930547","display_name":"Junfeng Li","orcid":"https://orcid.org/0000-0002-1207-3317"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Li","raw_affiliation_strings":["Ministry of Sports, Shandong Technology and Business University, Yantai 264005, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Sports, Shandong Technology and Business University, Yantai 264005, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101584006","display_name":"Jian Tian","orcid":"https://orcid.org/0000-0002-9535-4957"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Tian","raw_affiliation_strings":["School of Physical Education, Henan University, Kaifeng 475001, Henan, China"],"raw_orcid":"https://orcid.org/0000-0002-9535-4957","affiliations":[{"raw_affiliation_string":"School of Physical Education, Henan University, Kaifeng 475001, Henan, China","institution_ids":["https://openalex.org/I173899330"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101584006"],"corresponding_institution_ids":["https://openalex.org/I173899330"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":0.6595,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.70799781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9987999796867371,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9661999940872192,"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/key-frame","display_name":"Key frame","score":0.8702243566513062},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.8163800835609436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8140311241149902},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6895394325256348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6829391121864319},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6474196910858154},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5109726190567017},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4622281491756439},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43439921736717224},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4207890033721924},{"id":"https://openalex.org/keywords/athletes","display_name":"Athletes","score":0.4129839241504669},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4120520353317261},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.41060397028923035},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0784231424331665}],"concepts":[{"id":"https://openalex.org/C2780139006","wikidata":"https://www.wikidata.org/wiki/Q1493902","display_name":"Key frame","level":3,"score":0.8702243566513062},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.8163800835609436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140311241149902},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6895394325256348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6829391121864319},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6474196910858154},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5109726190567017},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4622281491756439},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43439921736717224},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4207890033721924},{"id":"https://openalex.org/C2781054738","wikidata":"https://www.wikidata.org/wiki/Q4813730","display_name":"Athletes","level":2,"score":0.4129839241504669},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4120520353317261},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.41060397028923035},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0784231424331665},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/1016574","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/1016574","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/1016574.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:853ed549884b4e22acb31a2726fde15f","is_oa":true,"landing_page_url":"https://doaj.org/article/853ed549884b4e22acb31a2726fde15f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scientific Programming, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/1016574","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/1016574","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/1016574.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3707763","display_name":null,"funder_award_id":"19CTYJ16","funder_id":"https://openalex.org/F4320336624","funder_display_name":"Social Science Planning Project of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320336624","display_name":"Social Science Planning Project of Shandong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3196724361.pdf","grobid_xml":"https://content.openalex.org/works/W3196724361.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1485974448","https://openalex.org/W1744759976","https://openalex.org/W1977177161","https://openalex.org/W2020719522","https://openalex.org/W2045221706","https://openalex.org/W2062097648","https://openalex.org/W2102605133","https://openalex.org/W2129291408","https://openalex.org/W2136922672","https://openalex.org/W2137983211","https://openalex.org/W2142194269","https://openalex.org/W2147328102","https://openalex.org/W2151103935","https://openalex.org/W2154579312","https://openalex.org/W2194345886","https://openalex.org/W2395611524","https://openalex.org/W2558383949","https://openalex.org/W2609930246","https://openalex.org/W2737677090","https://openalex.org/W2773676541","https://openalex.org/W2886735509","https://openalex.org/W2889227713","https://openalex.org/W2908469318","https://openalex.org/W2945034577","https://openalex.org/W2964206580","https://openalex.org/W3190260202"],"related_works":["https://openalex.org/W2394005538","https://openalex.org/W4391621807","https://openalex.org/W2366356402","https://openalex.org/W201407858","https://openalex.org/W2352751678","https://openalex.org/W2892592112","https://openalex.org/W2137350240","https://openalex.org/W2100571196","https://openalex.org/W1614340030","https://openalex.org/W2761431849"],"abstract_inverted_index":{"With":[0],"the":[1,7,23,41,67,73,89,100,110,127,140,149,166],"rapid":[2],"technological":[3],"advances":[4],"in":[5,26,76,175],"sports,":[6],"number":[8],"of":[9,32,43,91,96,102,113,157],"athletics":[10,24],"increases":[11],"gradually.":[12],"For":[13],"sports":[14,51,68,77],"professionals,":[15],"it":[16],"is":[17,85,123],"obligatory":[18],"to":[19,39,71,87,108,125],"oversee":[20],"and":[21,146,162,180],"explore":[22],"pose":[25,94,111,177,182],"athletes\u2019":[27],"training.":[28,78],"Key":[29],"frame":[30,120,169],"extraction":[31,121,170],"training":[33,45,69],"videos":[34],"plays":[35],"a":[36,50,80,103,117],"significant":[37],"role":[38],"ease":[40],"analysis":[42,163],"sport":[44],"videos.":[46],"This":[47],"paper":[48],"develops":[49],"actions\u2019":[52],"classification":[53,155],"system":[54],"for":[55],"accurately":[56],"classifying":[57],"athlete\u2019s":[58,150],"actions.":[59],"The":[60,135,159],"key":[61,119,128,168,176,181],"video":[62,70],"frames":[63,97,129],"are":[64],"extracted":[65],"from":[66],"highlight":[72],"distinct":[74,118],"actions":[75],"Subsequently,":[79],"fully":[81],"convolutional":[82],"network":[83,106],"(FCN)":[84],"used":[86],"extract":[88,126],"region":[90],"interest":[92],"(ROI)":[93],"detection":[95],"followed":[98],"by":[99],"application":[101],"convolution":[104],"neural":[105],"(CNN)":[107],"estimate":[109],"probability":[112,133,178],"each":[114],"frame.":[115],"Moreover,":[116],"approach":[122],"established":[124],"considering":[130],"neighboring":[131],"frames\u2019":[132],"differences.":[134],"experimental":[136,160],"results":[137,161],"determine":[138],"that":[139,165],"proposed":[141,167],"method":[142,171],"showed":[143],"better":[144],"performance":[145],"can":[147],"recognize":[148],"posture":[151],"with":[152],"an":[153],"average":[154],"rate":[156],"98%.":[158],"validate":[164],"outperforms":[172],"its":[173],"counterparts":[174],"estimation":[179],"extraction.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
