{"id":"https://openalex.org/W4388705055","doi":"https://doi.org/10.3991/ijim.v17i21.45201","title":"Improved Detection and Tracking of Objects Based on a Modified Deep Learning Model (YOLOv5)","display_name":"Improved Detection and Tracking of Objects Based on a Modified Deep Learning Model (YOLOv5)","publication_year":2023,"publication_date":"2023-11-15","ids":{"openalex":"https://openalex.org/W4388705055","doi":"https://doi.org/10.3991/ijim.v17i21.45201"},"language":"en","primary_location":{"id":"doi:10.3991/ijim.v17i21.45201","is_oa":true,"landing_page_url":"https://doi.org/10.3991/ijim.v17i21.45201","pdf_url":"https://online-journals.org/index.php/i-jim/article/download/45201/14191","source":{"id":"https://openalex.org/S4210177413","display_name":"International Journal of Interactive Mobile Technologies (iJIM)","issn_l":"1865-7923","issn":["1865-7923"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313744","host_organization_name":"kassel university press","host_organization_lineage":["https://openalex.org/P4310313744"],"host_organization_lineage_names":["kassel university press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Interactive Mobile Technologies (iJIM)","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://online-journals.org/index.php/i-jim/article/download/45201/14191","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001365732","display_name":"Nadia Ibrahim Nife","orcid":"https://orcid.org/0000-0002-4006-3773"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Nadia Ibrahim Nife","raw_affiliation_strings":["Control & Energy Management Laboratory, National School of Sfax Engineers (ENIS), University of Sfax, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Control & Energy Management Laboratory, National School of Sfax Engineers (ENIS), University of Sfax, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111075025","display_name":"Mohammed Chtourou","orcid":null},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohammed Chtourou","raw_affiliation_strings":["Control & Energy Management Laboratory, National School of Sfax Engineers (ENIS), University of Sfax, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Control & Energy Management Laboratory, National School of Sfax Engineers (ENIS), University of Sfax, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142899784"],"apc_list":{"value":260,"currency":"EUR","value_usd":280},"apc_paid":{"value":260,"currency":"EUR","value_usd":280},"fwci":0.4676,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.59687442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"17","issue":"21","first_page":"145","last_page":"160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9940000176429749,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9940000176429749,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9765999913215637,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9653000235557556,"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/computer-science","display_name":"Computer science","score":0.7508431673049927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.726740837097168},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6552614569664001},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6550332903862},{"id":"https://openalex.org/keywords/android","display_name":"Android (operating system)","score":0.5581924915313721},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.556088387966156},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5144999027252197},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49154624342918396},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44120529294013977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3282301425933838}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7508431673049927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.726740837097168},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6552614569664001},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6550332903862},{"id":"https://openalex.org/C557433098","wikidata":"https://www.wikidata.org/wiki/Q94","display_name":"Android (operating system)","level":2,"score":0.5581924915313721},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.556088387966156},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5144999027252197},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49154624342918396},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44120529294013977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3282301425933838},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3991/ijim.v17i21.45201","is_oa":true,"landing_page_url":"https://doi.org/10.3991/ijim.v17i21.45201","pdf_url":"https://online-journals.org/index.php/i-jim/article/download/45201/14191","source":{"id":"https://openalex.org/S4210177413","display_name":"International Journal of Interactive Mobile Technologies (iJIM)","issn_l":"1865-7923","issn":["1865-7923"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313744","host_organization_name":"kassel university press","host_organization_lineage":["https://openalex.org/P4310313744"],"host_organization_lineage_names":["kassel university press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Interactive Mobile Technologies (iJIM)","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3991/ijim.v17i21.45201","is_oa":true,"landing_page_url":"https://doi.org/10.3991/ijim.v17i21.45201","pdf_url":"https://online-journals.org/index.php/i-jim/article/download/45201/14191","source":{"id":"https://openalex.org/S4210177413","display_name":"International Journal of Interactive Mobile Technologies (iJIM)","issn_l":"1865-7923","issn":["1865-7923"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310313744","host_organization_name":"kassel university press","host_organization_lineage":["https://openalex.org/P4310313744"],"host_organization_lineage_names":["kassel university press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Interactive Mobile Technologies (iJIM)","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388705055.pdf","grobid_xml":"https://content.openalex.org/works/W4388705055.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2773689216","https://openalex.org/W2884754247","https://openalex.org/W2997408160","https://openalex.org/W3013211776","https://openalex.org/W3021970402","https://openalex.org/W3029515339","https://openalex.org/W3086583298","https://openalex.org/W3109992649","https://openalex.org/W3133882559","https://openalex.org/W3135294400","https://openalex.org/W3146332956","https://openalex.org/W3152382703","https://openalex.org/W3187053686","https://openalex.org/W3191773007","https://openalex.org/W3200676841","https://openalex.org/W3205490848","https://openalex.org/W4220681577","https://openalex.org/W4220960182","https://openalex.org/W4226108189","https://openalex.org/W4226474162","https://openalex.org/W4283029931","https://openalex.org/W4283691842","https://openalex.org/W4284969145","https://openalex.org/W4288435676","https://openalex.org/W4289861074","https://openalex.org/W4291819654","https://openalex.org/W4292793990","https://openalex.org/W4296900139"],"related_works":["https://openalex.org/W4285411112","https://openalex.org/W2085033728","https://openalex.org/W2171299904","https://openalex.org/W3034529322","https://openalex.org/W4390494008","https://openalex.org/W2922442631","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2055243143","https://openalex.org/W2113597336"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2],"seen":[3],"advances":[4],"in":[5,9,25,35,136,163,189,258],"deep":[6],"learning,":[7],"including":[8,41],"the":[10,26,32,48,56,59,67,70,87,114,132,146,151,176,183,190,201,259],"field":[11],"of":[12,23,31,46,50,58,69,113,134,148,150,186,203],"traffic":[13,83,219,238],"management.":[14],"Detecting":[15],"distant":[16,165],"objects":[17,51,121,171,187,199,205],"that":[18,270],"occupy":[19],"a":[20,79,82,97,240,246],"small":[21,167],"number":[22,185,202],"pixels":[24],"input":[27],"image":[28,101,152],"is":[29,76,244],"one":[30],"major":[33],"challenges":[34,45],"computer":[36],"vision":[37],"for":[38,102,267],"several":[39],"reasons,":[40],"limited":[42],"resolution.":[43],"The":[44,73,158,208],"detecting":[47,119,164,197],"rotation":[49,149],"may":[52],"be":[53,225,250,272],"attributed":[54],"to":[55,77,109,118,127,155,175,232],"deflection":[57],"camera":[60],"when":[61],"taking":[62],"photographs.":[63],"We":[64],"recommend":[65],"enhancing":[66],"features":[68],"YOLOv5":[71,178],"network.":[72],"proposed":[74],"method":[75],"train":[78],"model":[80,223],"on":[81,96,227,264,274],"dataset,":[84],"which":[85],"achieves":[86],"best":[88,184],"inference":[89,209],"results":[90,159],"through":[91],"training,":[92],"testing,":[93],"and":[94,142,166,194,196,255],"detection":[95,269],"1280":[98,100],"\u00d7":[99],"300":[103],"epochs.":[104],"Moreover,":[105],"modifications":[106],"were":[107,172],"made":[108],"some":[110],"structural":[111],"elements":[112],"YOLOv5.":[115],"In":[116,144],"addition":[117],"round":[120],"by":[122],"increasing":[123],"degrees":[124],"from":[125],"0":[126],"270,":[128],"it":[129],"also":[130],"increases":[131,200],"probability":[133],"flipping":[135],"all":[137],"directions:":[138],"up,":[139],"down,":[140],"left,":[141],"right.":[143],"addition,":[145],"degree":[147],"was":[153,211],"increased":[154],"90":[156],"degrees.":[157],"showed":[160],"optimized":[161],"accuracy":[162],"objects,":[168],"as":[169],"73":[170],"detected":[173,188,204],"compared":[174],"original":[177],"23":[179],"objects.":[180],"It":[181],"achieved":[182],"video":[191],"(people,":[192],"cars,":[193],"others),":[195],"rotating":[198],"(32":[206],"objects).":[207],"time":[210,254],"(23":[212],"Ms.)":[213],"this":[214],"dataset":[215],"can":[216,224,249,271],"make":[217],"excellent":[218],"monitoring":[220],"applications.":[221],"This":[222,243],"deployed":[226],"an":[228],"Android":[229],"mobile":[230,247,275],"device":[231,248],"provide":[233],"accurate":[234],"data":[235],"about":[236],"current":[237],"at":[239,252],"specific":[241],"location.":[242],"because":[245],"used":[251],"any":[253],"place.":[256],"Therefore,":[257],"future,":[260],"we":[261],"are":[262],"working":[263],"designing":[265],"models":[266],"object":[268],"operated":[273],"devices.":[276]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
