{"id":"https://openalex.org/W4388405531","doi":"https://doi.org/10.1109/kse59128.2023.10299493","title":"A Fitness Movement Evaluation System Using Deep Learning","display_name":"A Fitness Movement Evaluation System Using Deep Learning","publication_year":2023,"publication_date":"2023-10-18","ids":{"openalex":"https://openalex.org/W4388405531","doi":"https://doi.org/10.1109/kse59128.2023.10299493"},"language":"en","primary_location":{"id":"doi:10.1109/kse59128.2023.10299493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse59128.2023.10299493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-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/A5001591873","display_name":"Chin-Chih Chang","orcid":"https://orcid.org/0000-0001-8752-4859"},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chin-Chih Chang","raw_affiliation_strings":["Chung Hua University,Department of Computer Science and Information Engineering,Hsinchu City,Taiwan","Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Chung Hua University,Department of Computer Science and Information Engineering,Hsinchu City,Taiwan","institution_ids":["https://openalex.org/I59460038"]},{"raw_affiliation_string":"Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009781937","display_name":"Chi-Hung Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Hung Wei","raw_affiliation_strings":["Ph.D. Program in Engineering Science Chung Hua University,Hsinchu City,Taiwan","Ph.D. Program in Engineering Science Chung Hua University, Hsinchu City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Ph.D. Program in Engineering Science Chung Hua University,Hsinchu City,Taiwan","institution_ids":["https://openalex.org/I59460038"]},{"raw_affiliation_string":"Ph.D. Program in Engineering Science Chung Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057165069","display_name":"Haowei Wu","orcid":"https://orcid.org/0000-0002-5175-8335"},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hao-Wei Wu","raw_affiliation_strings":["Chung Hua University,Department of Computer Science and Information Engineering,Hsinchu City,Taiwan","Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Chung Hua University,Department of Computer Science and Information Engineering,Hsinchu City,Taiwan","institution_ids":["https://openalex.org/I59460038"]},{"raw_affiliation_string":"Department of Computer Science and Information Engineering, Chung Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036321759","display_name":"Sean Hsiao","orcid":null},"institutions":[{"id":"https://openalex.org/I59460038","display_name":"Chung Hua University","ror":"https://ror.org/01yzz0f51","country_code":"TW","type":"education","lineage":["https://openalex.org/I59460038"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sean Hsiao","raw_affiliation_strings":["Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University,Hsinchu City,Taiwan","Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University, Hsinchu City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University,Hsinchu City,Taiwan","institution_ids":["https://openalex.org/I59460038"]},{"raw_affiliation_string":"Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University, Hsinchu City, Taiwan","institution_ids":["https://openalex.org/I59460038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5001591873"],"corresponding_institution_ids":["https://openalex.org/I59460038"],"apc_list":null,"apc_paid":null,"fwci":0.1228,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43272761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9947999715805054,"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":0.9947999715805054,"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":0.9437999725341797,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7570139169692993},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.724195122718811},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6881195306777954},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5408511757850647},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5359920263290405},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.516316831111908},{"id":"https://openalex.org/keywords/fitness-approximation","display_name":"Fitness approximation","score":0.4198191463947296},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41971856355667114},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.2267221212387085},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.18822982907295227}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7570139169692993},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.724195122718811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6881195306777954},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5408511757850647},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5359920263290405},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.516316831111908},{"id":"https://openalex.org/C148392497","wikidata":"https://www.wikidata.org/wiki/Q16250539","display_name":"Fitness approximation","level":4,"score":0.4198191463947296},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41971856355667114},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2267221212387085},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.18822982907295227},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kse59128.2023.10299493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kse59128.2023.10299493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Knowledge and Systems Engineering (KSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2112796928","https://openalex.org/W2113325037","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2559085405","https://openalex.org/W2963037989","https://openalex.org/W2963446712","https://openalex.org/W2971627998","https://openalex.org/W3208970891","https://openalex.org/W4245888765","https://openalex.org/W4287755748","https://openalex.org/W4289529983","https://openalex.org/W4297997614","https://openalex.org/W6684191040","https://openalex.org/W6730277886","https://openalex.org/W6779739588"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W39808511","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"This":[0],"paper":[1,94],"proposes":[2],"a":[3,14,45,83,98,103,126],"fitness":[4,26,50,77,87,107,115,130,138],"movement":[5],"evaluation":[6],"system":[7,12,41,57,67,81,123],"using":[8],"deep":[9,15],"learning.":[10],"The":[11,28,40,52,66,79,89,122],"uses":[13],"convolutional":[16],"neural":[17],"network":[18],"(CNN)":[19],"to":[20,33,70,73,96,100,143],"extract":[21],"features":[22,29],"from":[23],"pictures":[24,48],"of":[25,47,49,92],"movements.":[27,51,78],"are":[30],"then":[31],"used":[32],"classify":[34,60],"the":[35,56,61],"movements":[36,62],"into":[37,63],"different":[38,64],"categories.":[39,65],"is":[42,68,82,95,124],"evaluated":[43],"on":[44,75],"dataset":[46],"results":[53],"show":[54],"that":[55],"can":[58,110,133],"accurately":[59],"designed":[69],"provide":[71,141],"feedback":[72,142],"users":[74,102,112],"their":[76,106,114,118,144],"proposed":[80],"valuable":[84,127],"tool":[85,128],"for":[86,105,129],"enthusiasts.":[88],"main":[90],"contribution":[91],"this":[93],"propose":[97],"way":[99],"give":[101],"score":[104],"movement.":[108],"It":[109,132],"help":[111,134],"improve":[113],"and":[116,140],"track":[117],"progress":[119],"over":[120],"time.":[121],"also":[125],"professionals.":[131],"professionals":[135],"develop":[136],"new":[137],"programs":[139],"clients.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}