{"id":"https://openalex.org/W7143005608","doi":"https://doi.org/10.1007/s44163-026-00985-y","title":"Table tennis detection and trajectory prediction based on shuffle-YOLOv5s algorithm","display_name":"Table tennis detection and trajectory prediction based on shuffle-YOLOv5s algorithm","publication_year":2026,"publication_date":"2026-03-29","ids":{"openalex":"https://openalex.org/W7143005608","doi":"https://doi.org/10.1007/s44163-026-00985-y"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-026-00985-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-00985-y","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44163-026-00985-y","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130873676","display_name":"Yuxue Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210097552","display_name":"Handan Polytechnic College","ror":"https://ror.org/00vna7491","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097552"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxue Wang","raw_affiliation_strings":["Department of Fundamental Courses, Laiwu Vocational and Technical College, Jinan, 271199, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Fundamental Courses, Laiwu Vocational and Technical College, Jinan, 271199, China","institution_ids":["https://openalex.org/I4210097552"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5146791969","display_name":"Yingying Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210097552","display_name":"Handan Polytechnic College","ror":"https://ror.org/00vna7491","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210097552"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingying Yang","raw_affiliation_strings":["Department of Fundamental Courses, Laiwu Vocational and Technical College, Jinan, 271199, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Fundamental Courses, Laiwu Vocational and Technical College, Jinan, 271199, China","institution_ids":["https://openalex.org/I4210097552"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5130873676"],"corresponding_institution_ids":["https://openalex.org/I4210097552"],"apc_list":{"value":1340,"currency":"USD","value_usd":1340},"apc_paid":{"value":1340,"currency":"USD","value_usd":1340},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33499976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.24060000479221344,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.24060000479221344,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.16940000653266907,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.040800001472234726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7390000224113464},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.7275000214576721},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.501800000667572},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.48989999294281006},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.484499990940094},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4480000138282776},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4300999939441681},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42100000381469727}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7390000224113464},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.7275000214576721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535000205039978},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6362000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6089000105857849},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.501800000667572},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.484499990940094},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4406999945640564},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4300999939441681},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.38909998536109924},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3837999999523163},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.3456000089645386},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.3310000002384186},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.26759999990463257},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.26019999384880066},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-026-00985-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-00985-y","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7ddf764f9d8b4779b66c0379b9050613","is_oa":true,"landing_page_url":"https://doaj.org/article/7ddf764f9d8b4779b66c0379b9050613","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":"Discover Artificial Intelligence, Vol 6, Iss 1 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-026-00985-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-026-00985-y","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W4220894661","https://openalex.org/W4283076857","https://openalex.org/W4361285851","https://openalex.org/W4362562906","https://openalex.org/W4368365607","https://openalex.org/W4382345441","https://openalex.org/W4383673562","https://openalex.org/W4384559456","https://openalex.org/W4385357628","https://openalex.org/W4386091971","https://openalex.org/W4387623836","https://openalex.org/W4388637501","https://openalex.org/W4388978441","https://openalex.org/W4389987328","https://openalex.org/W4390823374","https://openalex.org/W4391516379","https://openalex.org/W4394773642","https://openalex.org/W4399383167","https://openalex.org/W4399526727","https://openalex.org/W4400033369","https://openalex.org/W4400732561","https://openalex.org/W4400770643","https://openalex.org/W4403390493","https://openalex.org/W4404334328","https://openalex.org/W4404368533","https://openalex.org/W4404719272","https://openalex.org/W4407508421","https://openalex.org/W4407748921","https://openalex.org/W4410468618"],"related_works":[],"abstract_inverted_index":{"Table":[0],"tennis":[1,109,170,181],"has":[2,153],"the":[3,22,28,67,80,114,123,130,144,151,160],"characteristics":[4],"of":[5,24,30,71,82,107,118,143,162,168],"small":[6,31,44,86],"size":[7,57],"and":[8,11,26,51,62,73,105,129,165,174,183],"high":[9],"speed,":[10],"existing":[12],"object":[13,45],"detection":[14,124,133,164],"algorithms":[15],"have":[16],"low":[17],"recognition":[18],"accuracy.":[19],"To":[20],"address":[21],"problem":[23],"detecting":[25],"predicting":[27],"trajectory":[29,47,166],"objects":[32],"in":[33,85,171],"high-speed":[34,172],"motion,":[35,173],"this":[36,119],"paper":[37],"presents":[38],"an":[39,75],"intelligent":[40],"prediction":[41,106],"model":[42,54,120,152],"for":[43,179],"motion":[46,83],"based":[48],"on":[49],"ShuffleNet":[50],"YOLOv5s.":[52],"The":[53],"reduces":[55],"parameter":[56],"by":[58],"using":[59],"grouped":[60],"convolution":[61],"channel":[63],"shuffle.":[64],"It":[65,88],"combines":[66],"dual-stage":[68],"association":[69],"matching":[70],"ByteTrack":[72],"applies":[74],"unscented":[76],"transform":[77],"to":[78,95,101],"reduce":[79],"interference":[81],"blur":[84],"objects.":[87],"also":[89],"uses":[90],"a":[91],"Gated":[92],"Recurrent":[93],"Unit":[94],"capture":[96],"temporal":[97],"dependence,":[98],"so":[99],"as":[100],"achieve":[102],"adaptive":[103],"tracking":[104,167],"table":[108,169,180],"trajectory.":[110],"In":[111],"test":[112],"experiments,":[113],"average":[115],"classification":[116],"accuracy":[117,134],"is":[121,126,135,138],"98.05%,":[122],"speed":[125],"522.5":[127],"fps,":[128],"landing":[131],"point":[132],"98.21%,":[136],"which":[137],"significantly":[139],"higher":[140],"than":[141],"those":[142],"compared":[145],"models.":[146],"These":[147],"results":[148],"show":[149],"that":[150],"more":[154],"efficient":[155],"lightweight":[156],"computing":[157],"ability,":[158],"meets":[159],"demand":[161],"real-time":[163],"provides":[175],"reliable":[176],"algorithm":[177],"support":[178],"training":[182],"match":[184],"data":[185],"analysis.":[186]},"counts_by_year":[],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-03-30T00:00:00"}
