{"id":"https://openalex.org/W4400115141","doi":"https://doi.org/10.3233/idt-230733","title":"Exploring the application of automatic distance measurement for standing long jump based on image denoising and area detection","display_name":"Exploring the application of automatic distance measurement for standing long jump based on image denoising and area detection","publication_year":2024,"publication_date":"2024-06-28","ids":{"openalex":"https://openalex.org/W4400115141","doi":"https://doi.org/10.3233/idt-230733"},"language":"en","primary_location":{"id":"doi:10.3233/idt-230733","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230733","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-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/A5032463559","display_name":"Yunjun Wang","orcid":"https://orcid.org/0000-0001-9286-281X"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunjun Wang","raw_affiliation_strings":["Teaching Department of Sports, Henan Polytechnic Institute, Nanyang, China"],"affiliations":[{"raw_affiliation_string":"Teaching Department of Sports, Henan Polytechnic Institute, Nanyang, China","institution_ids":["https://openalex.org/I4210166499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002534655","display_name":"Zhiyuan Ren","orcid":"https://orcid.org/0000-0003-4560-5102"},"institutions":[{"id":"https://openalex.org/I4210166499","display_name":"Henan Polytechnic University","ror":"https://ror.org/05vr1c885","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210166499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Ren","raw_affiliation_strings":["School of Electronic Information Engineering, Henan Polytechnic Institute, Nanyang, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Information Engineering, Henan Polytechnic Institute, Nanyang, China","institution_ids":["https://openalex.org/I4210166499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032463559"],"corresponding_institution_ids":["https://openalex.org/I4210166499"],"apc_list":null,"apc_paid":null,"fwci":0.849,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7469869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"18","issue":"4","first_page":"2977","last_page":"2992"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13176","display_name":"Winter Sports Injuries and Performance","score":0.9736999869346619,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T13176","display_name":"Winter Sports Injuries and Performance","score":0.9736999869346619,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12994","display_name":"Infrared Thermography in Medicine","score":0.9545999765396118,"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"}},{"id":"https://openalex.org/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9409000277519226,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7056927680969238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6755884289741516},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5697180032730103},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5537034869194031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5453353524208069},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4969506561756134},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44216835498809814},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43226537108421326},{"id":"https://openalex.org/keywords/step-detection","display_name":"Step detection","score":0.4259647727012634},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.42258840799331665},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.41766875982284546},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29428189992904663},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2196727693080902},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10445955395698547}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7056927680969238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6755884289741516},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5697180032730103},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5537034869194031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5453353524208069},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4969506561756134},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44216835498809814},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43226537108421326},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.4259647727012634},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.42258840799331665},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.41766875982284546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29428189992904663},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2196727693080902},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10445955395698547},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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:10.3233/idt-230733","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230733","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2775517272","https://openalex.org/W2795861748","https://openalex.org/W2809694239","https://openalex.org/W2897926844","https://openalex.org/W2899589943","https://openalex.org/W2910533598","https://openalex.org/W2911289513","https://openalex.org/W2935920628","https://openalex.org/W2949230211","https://openalex.org/W2965631297","https://openalex.org/W3011349357","https://openalex.org/W3015009731","https://openalex.org/W3038745890","https://openalex.org/W3040935415","https://openalex.org/W3136218483","https://openalex.org/W3148496600","https://openalex.org/W3185030651","https://openalex.org/W3187556646","https://openalex.org/W4282967251","https://openalex.org/W4287883290","https://openalex.org/W4290725197","https://openalex.org/W4298129503","https://openalex.org/W4312090427","https://openalex.org/W4381986044","https://openalex.org/W4387806264"],"related_works":["https://openalex.org/W4362581794","https://openalex.org/W2536049644","https://openalex.org/W2387796150","https://openalex.org/W2139368882","https://openalex.org/W3083008816","https://openalex.org/W2348643679","https://openalex.org/W3196104895","https://openalex.org/W2356107741","https://openalex.org/W2070967616","https://openalex.org/W2892043599"],"abstract_inverted_index":{"Traditional":[0],"standing":[1,103,305],"long":[2,32,104,175,290,306],"jump":[3,33,105,176,291],"measurement":[4,43,66,78,131,178,261,292,317],"relies":[5],"only":[6],"on":[7,53],"visual":[8],"reading":[9],"and":[10,20,29,39,45,64,120,140,161,171,186,199,256,266,274],"manual":[11],"recording,":[12],"which":[13,210],"makes":[14],"the":[15,27,37,48,55,69,77,86,93,100,110,115,126,145,166,191,215,221,228,233,238,247,260,267,281,295,299,304,323,331],"recording":[16],"of":[17,31,41,50,79,88,102,112,117,128,147,154,168,182,208,223,232,249,263,280,301,333],"data":[18],"subjective":[19,51],"arbitrary,":[21],"making":[22],"it":[23],"difficult":[24],"to":[25,46,58,85,143,164,297],"ensure":[26],"accuracy":[28,207],"efficiency":[30,300],"performance.":[34],"To":[35],"address":[36],"shortcomings":[38],"deficiencies":[40],"traditional":[42,315],"methods":[44],"avoid":[47],"interference":[49],"bias":[52],"results,":[54],"research":[56,70],"aims":[57],"provide":[59,72],"a":[60,129,173,205,244,311],"more":[61],"accurate,":[62],"automated,":[63],"objective":[65],"method.":[67],"Furthermore,":[68],"will":[71],"new":[73],"technological":[74],"means":[75,329],"for":[76,303,330],"related":[80],"sports":[81,334],"projects.":[82,336],"In":[83,220],"contrast":[84],"utilization":[87],"human":[89],"motion":[90],"recognition":[91,97],"technology,":[92],"study":[94,192,239],"introduces":[95],"image":[96,118,155],"technology":[98,108],"into":[99],"domain":[101],"testing.":[106],"This":[107,319],"enables":[109],"calculation":[111],"distance":[113,130,177,316],"through":[114],"application":[116],"processing":[119],"perspective":[121],"transformation":[122],"algorithms,":[123],"thereby":[124],"facilitating":[125],"realization":[127],"function.":[132],"Specifically,":[133],"this":[134,264],"includes":[135],"using":[136],"wavelet":[137,148,183],"decomposition":[138,184],"coefficients":[139,185],"morphological":[141,187],"denoising":[142,188],"improve":[144],"performance":[146],"threshold":[149],"denoising,":[150],"achieving":[151],"feature":[152,225],"extraction":[153],"edge":[156],"information,":[157],"adding":[158],"vibration":[159],"sensors":[160],"CNN":[162],"algorithms":[163],"adjust":[165],"angle":[167],"offset":[169],"images,":[170],"designing":[172],"multi-step":[174],"system.":[179],"The":[180,253,277,288],"combination":[181],"utilized":[189],"in":[190,237,246],"demonstrated":[193],"lower":[194],"mean":[195],"square":[196],"error":[197],"(50.8369)":[198],"signal-to-noise":[200],"ratio":[201],"(24.1126)":[202],"values,":[203],"with":[204,243,314],"maximum":[206],"96.23%,":[209],"was":[211,283],"significantly":[212],"higher":[213],"than":[214],"other":[216],"two":[217],"comparison":[218],"methods.":[219],"context":[222],"different":[224],"information":[226],"recognition,":[227],"ROC":[229],"curve":[230],"area":[231],"algorithm":[234],"model":[235],"proposed":[236,289],"reached":[240],"over":[241],"85%,":[242],"deviation":[245,279],"dataset":[248],"all":[250],"below":[251],"0.5.":[252],"minimum":[254],"absolute":[255],"relative":[257],"errors":[258],"between":[259],"results":[262,270],"method":[265],"actual":[268],"test":[269],"were":[271],"0.01":[272],"cm":[273],"2%,":[275],"respectively.":[276],"overall":[278],"system":[282,293],"0.35,":[284],"indicating":[285],"high":[286],"stability.":[287],"has":[294],"potential":[296],"enhance":[298],"testing":[302],"jump,":[307],"while":[308],"also":[309],"forming":[310],"complementary":[312],"mode":[313],"systems.":[318],"could":[320],"collectively":[321],"serve":[322],"intelligent":[324],"instrument":[325],"market,":[326],"providing":[327],"technical":[328],"development":[332],"teaching":[335]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-24T08:02:53.985720","created_date":"2025-10-10T00:00:00"}
