{"id":"https://openalex.org/W4391489228","doi":"https://doi.org/10.3233/idt-230545","title":"Number detection of cylindrical objects based on improved Yolov5s algorithm","display_name":"Number detection of cylindrical objects based on improved Yolov5s algorithm","publication_year":2024,"publication_date":"2024-01-09","ids":{"openalex":"https://openalex.org/W4391489228","doi":"https://doi.org/10.3233/idt-230545"},"language":"en","primary_location":{"id":"doi:10.3233/idt-230545","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230545","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/A5100678713","display_name":"Yachao Wang","orcid":"https://orcid.org/0000-0002-6473-6856"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yachao Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015896362","display_name":"Yaju Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaju Liu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109652073","display_name":"Dongxuan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongxuan Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089042848","display_name":"Yu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100678713"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01029555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"1","first_page":"441","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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":0.9991999864578247,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.991599977016449,"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/initialization","display_name":"Initialization","score":0.7578352689743042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6921526789665222},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.640400230884552},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6140543222427368},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.597636342048645},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5696280002593994},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5202528238296509},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5114392042160034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4844122529029846},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4717947840690613},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.465646356344223},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44867444038391113},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4177497327327728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3864210546016693},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3359746038913727},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2804579734802246},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12919634580612183},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12443757057189941}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7578352689743042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6921526789665222},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.640400230884552},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6140543222427368},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.597636342048645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5696280002593994},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5202528238296509},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5114392042160034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4844122529029846},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4717947840690613},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.465646356344223},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44867444038391113},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4177497327327728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3864210546016693},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3359746038913727},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2804579734802246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12919634580612183},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12443757057189941},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-230545","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230545","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":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2109255472","https://openalex.org/W2193145675","https://openalex.org/W2272004637","https://openalex.org/W2570343428","https://openalex.org/W2579985080","https://openalex.org/W2743473392","https://openalex.org/W2783152060","https://openalex.org/W2896078131","https://openalex.org/W2901807041","https://openalex.org/W2949533892","https://openalex.org/W2963037989","https://openalex.org/W2985936223","https://openalex.org/W2990268359","https://openalex.org/W2990763144","https://openalex.org/W3003732786","https://openalex.org/W3006312951","https://openalex.org/W3008125552","https://openalex.org/W3018757597","https://openalex.org/W3106250896","https://openalex.org/W3177052299","https://openalex.org/W3191773007","https://openalex.org/W3194790201","https://openalex.org/W3209854808","https://openalex.org/W4206314365","https://openalex.org/W4281790833","https://openalex.org/W4287825176","https://openalex.org/W4293377385","https://openalex.org/W4293584584","https://openalex.org/W4297676427","https://openalex.org/W4297734170","https://openalex.org/W4301076899","https://openalex.org/W4320803135","https://openalex.org/W4386076325","https://openalex.org/W4394669457"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W183202219","https://openalex.org/W3095877357","https://openalex.org/W2072565696","https://openalex.org/W2050451745","https://openalex.org/W2378903222"],"abstract_inverted_index":{"As":[0],"deep":[1],"learning":[2],"continues":[3],"to":[4,85,108,129,136,173,187,239],"advance,":[5],"object":[6,54,290,308],"detection":[7,55,260,291],"technology":[8,56],"holds":[9],"potential":[10],"and":[11,29,44,65,164,178,226,271,299],"promising":[12],"prospects":[13],"in":[14,23,134,171,205,289],"the":[15,78,87,96,102,110,114,118,121,130,138,148,155,158,165,168,176,189,193,201,240,244,252,265,272,279,305],"recognition":[16,181],"of":[17,49,53,77,89,104,117,140,150,157,167,192,211,218,224,230,250,258,287,295,307],"cylindrical":[18,91],"objects\u2019":[19],"quantity,":[20],"such":[21],"as":[22,126],"industries":[24],"like":[25],"timber":[26],"processing,":[27],"construction,":[28],"pipeline":[30],"engineering.":[31],"The":[32,51,196,232],"traditional":[33],"manual":[34],"counting":[35,90],"methods":[36],"have":[37],"lower":[38],"efficiency,":[39,64],"a":[40,46,74,151,215,222,228,255,283],"higher":[41],"error":[42],"rate,":[43],"demand":[45],"greater":[47],"amount":[48],"manpower.":[50],"introduction":[52],"can":[57],"effectively":[58],"address":[59],"these":[60],"issues,":[61],"enhance":[62,137,179],"work":[63],"reduce":[66],"labor":[67],"costs.":[68],"Therefore,":[69],"this":[70,206],"research":[71],"paper":[72,94],"introduces":[73],"novel":[75],"variant":[76],"YOLOv5s":[79,242],"algorithm,":[80],"called":[81],"YOLOv5-COC,":[82],"specifically":[83],"designed":[84],"tackle":[86],"task":[88,306],"objects.":[92],"This":[93],"makes":[95],"following":[97],"significant":[98],"contributions:":[99],"Firstly,":[100],"introducing":[101],"utilization":[103],"data":[105],"augmentation":[106],"techniques":[107],"augment":[109],"dataset,":[111],"thereby":[112],"enhancing":[113],"generalization":[115],"ability":[116],"model.":[119],"Secondly,":[120],"K-means+\u2063+":[122],"algorithm":[123,133],"is":[124],"employed":[125],"an":[127,209,248],"alternative":[128],"conventional":[131],"K-means":[132],"order":[135,172],"initialization":[139],"anchor":[141],"boxes.":[142],"Thirdly,":[143],"introduce":[144],"distinct":[145],"methodologies,":[146],"including":[147],"incorporation":[149],"coordinated":[152],"attention":[153],"mechanism,":[154],"amalgamation":[156],"Bidirectional":[159],"Feature":[160],"Pyramid":[161],"Network":[162],"(BiFPN),":[163],"substitution":[166],"loss":[169],"function,":[170],"further":[174],"refine":[175],"model":[177,203,281],"its":[180],"precision.":[182],"Finally,":[183],"employ":[184],"ablation":[185],"experiments":[186],"assess":[188],"optimization":[190],"outcomes":[191],"aforementioned":[194],"methodologies.":[195],"experimental":[197],"results":[198],"reveal":[199],"that":[200],"YOLOv5-COC":[202,280],"proposed":[204],"study":[207],"attains":[208,221],"mAP":[210,245],"98.7%,":[212],"operates":[213],"at":[214,235],"frame":[216],"rate":[217,267],"60":[219],"FPS,":[220],"Precision":[223],"98.3%,":[225],"boasts":[227],"Recall":[229],"99.1%.":[231],"mAP@0.5:0.95":[233,273],"stands":[234],"72.4%.":[236],"In":[237,277],"comparison":[238],"original":[241],"model,":[243],"value":[246],"exhibits":[247],"improvement":[249],"1.3%,":[251],"FPS":[253],"experiences":[254],"remarkable":[256],"surge":[257],"27.7%,":[259],"accuracy":[261,288],"elevates":[262],"by":[263,269,275],"1%,":[264,270],"recall":[266],"advances":[268],"escalates":[274],"3.5%.":[276],"summary,":[278],"demonstrates":[282],"sufficiently":[284],"high":[285],"level":[286],"tasks,":[292],"mitigating":[293],"instances":[294],"both":[296],"false":[297,300],"negatives":[298],"positives.":[301],"It":[302],"efficiently":[303],"accomplishes":[304],"detection.":[309]},"counts_by_year":[],"updated_date":"2026-03-04T07:04:00.330322","created_date":"2025-10-10T00:00:00"}
