{"id":"https://openalex.org/W4394891680","doi":"https://doi.org/10.3390/s24082560","title":"Large Span Sizes and Irregular Shapes Target Detection Methods Using Variable Convolution-Improved YOLOv8","display_name":"Large Span Sizes and Irregular Shapes Target Detection Methods Using Variable Convolution-Improved YOLOv8","publication_year":2024,"publication_date":"2024-04-17","ids":{"openalex":"https://openalex.org/W4394891680","doi":"https://doi.org/10.3390/s24082560","pmid":"https://pubmed.ncbi.nlm.nih.gov/38676177"},"language":"en","primary_location":{"id":"doi:10.3390/s24082560","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24082560","pdf_url":"https://www.mdpi.com/1424-8220/24/8/2560/pdf?version=1713341067","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/8/2560/pdf?version=1713341067","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064129376","display_name":"Yan Gao","orcid":"https://orcid.org/0009-0007-0505-5018"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Gao","raw_affiliation_strings":["School of Intergated Circuits, Dalian University of Technology, Dalian 116024, China"],"affiliations":[{"raw_affiliation_string":"School of Intergated Circuits, Dalian University of Technology, Dalian 116024, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431792","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3865-8145"},"institutions":[{"id":"https://openalex.org/I4210126301","display_name":"Taiyuan Iron and Steel Group (China)","ror":"https://ror.org/03p16v381","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126301"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Automation Department, Lingyuan Iron and Steel Group Co., Ltd., Lingyuan 122500, China"],"affiliations":[{"raw_affiliation_string":"Automation Department, Lingyuan Iron and Steel Group Co., Ltd., Lingyuan 122500, China","institution_ids":["https://openalex.org/I4210126301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073227246","display_name":"Hsiang\u2010Chen Chui","orcid":"https://orcid.org/0000-0001-5154-2000"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]},{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hsiang-Chen Chui","raw_affiliation_strings":["School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China"],"affiliations":[{"raw_affiliation_string":"School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, China","institution_ids":["https://openalex.org/I4210092944","https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100420359","display_name":"Xiaoming Chen","orcid":"https://orcid.org/0000-0002-5717-8438"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoming Chen","raw_affiliation_strings":["School of Intergated Circuits, Dalian University of Technology, Dalian 116024, China"],"affiliations":[{"raw_affiliation_string":"School of Intergated Circuits, Dalian University of Technology, Dalian 116024, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100420359"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":2.9057,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.91890109,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"24","issue":"8","first_page":"2560","last_page":"2560"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9972000122070312,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9822999835014343,"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/computation","display_name":"Computation","score":0.6019719839096069},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6006296873092651},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5659131407737732},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5599866509437561},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5333630442619324},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.5081443786621094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.448219895362854},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.42958173155784607},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.42545580863952637},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.42397430539131165},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.42253977060317993},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4064873456954956},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2615865170955658},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1855630874633789},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.1227138340473175}],"concepts":[{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6019719839096069},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6006296873092651},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5659131407737732},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5599866509437561},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5333630442619324},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5081443786621094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.448219895362854},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.42958173155784607},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.42545580863952637},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.42397430539131165},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.42253977060317993},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4064873456954956},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2615865170955658},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1855630874633789},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.1227138340473175},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24082560","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24082560","pdf_url":"https://www.mdpi.com/1424-8220/24/8/2560/pdf?version=1713341067","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:38676177","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38676177","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11054827","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11054827","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:b23b0905279a4a658c77538c3697b88e","is_oa":true,"landing_page_url":"https://doaj.org/article/b23b0905279a4a658c77538c3697b88e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 8, p 2560 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24082560","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24082560","pdf_url":"https://www.mdpi.com/1424-8220/24/8/2560/pdf?version=1713341067","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394891680.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W2381216702","https://openalex.org/W2601564443","https://openalex.org/W2806070179","https://openalex.org/W2904472017","https://openalex.org/W2934625602","https://openalex.org/W2944223741","https://openalex.org/W2947833581","https://openalex.org/W2963037989","https://openalex.org/W2966407117","https://openalex.org/W3017330333","https://openalex.org/W3045829612","https://openalex.org/W3112710011","https://openalex.org/W3128730996","https://openalex.org/W3134194416","https://openalex.org/W3134746171","https://openalex.org/W3137769486","https://openalex.org/W3147578560","https://openalex.org/W3159402138","https://openalex.org/W3162335932","https://openalex.org/W3166716987","https://openalex.org/W3179724909","https://openalex.org/W4224297527","https://openalex.org/W4226373749","https://openalex.org/W4322772030","https://openalex.org/W4372279253","https://openalex.org/W4380325108","https://openalex.org/W4380684511","https://openalex.org/W4385415745","https://openalex.org/W4385688622","https://openalex.org/W4388077320","https://openalex.org/W6791329947"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2894651257","https://openalex.org/W3200590620","https://openalex.org/W4200172193","https://openalex.org/W4303926741","https://openalex.org/W3112165785"],"abstract_inverted_index":{"In":[0,99],"this":[1],"work,":[2],"an":[3],"object":[4],"detection":[5,86,108,144],"method":[6],"using":[7],"variable":[8],"convolution-improved":[9],"YOLOv8":[10,233],"is":[11,58,109,124,193],"proposed":[12],"to":[13,60,69,84,101,111,126,136,157,160,182],"solve":[14,102],"the":[15,32,35,41,50,61,67,73,76,81,85,89,103,117,127,134,137,143,147,151,161,166,169,173,185,190,202,212,231,237,243,253,262],"problem":[16,74,174],"of":[17,34,38,44,52,75,80,91,130,146,168,175,189,220,222,265],"low":[18,21,42],"accuracy":[19,145],"and":[20,26,49,88,93,114,225,251],"efficiency":[22],"in":[23],"detecting":[24],"spanning":[25],"irregularly":[27],"shaped":[28],"samples.":[29],"Aiming":[30],"at":[31],"problems":[33],"irregular":[36],"shape":[37],"a":[39,54,217],"target,":[40],"resolution":[43],"labeling":[45],"frames,":[46],"dense":[47],"distribution,":[48],"ease":[51],"overlap,":[53],"deformable":[55],"convolution":[56],"module":[57,123,153],"added":[59,125],"original":[62,162],"backbone":[63,128,191],"network.":[64],"This":[65],"allows":[66],"model":[68,177,235],"deal":[70],"flexibly":[71],"with":[72,195],"insufficient":[77],"perceptual":[78],"field":[79],"target":[82,107],"corresponding":[83],"point,":[87],"situations":[90],"leakage":[92],"misdetection":[94],"can":[95,180],"be":[96],"effectively":[97],"improved.":[98],"order":[100],"issue":[104],"that":[105,179,230],"small":[106],"susceptible":[110],"image":[112],"background":[113],"noise":[115],"interference,":[116],"Sim-AM":[118,152],"(simple":[119],"parameter-free":[120],"attention":[121,135],"mechanism)":[122],"network":[129,192,234],"YOLOv8,":[131],"which":[132,164,199,260],"enhances":[133],"underlying":[138],"features":[139],"and,":[140],"thus,":[141],"improves":[142,236],"model.":[148,170],"More":[149],"importantly,":[150],"does":[154],"not":[155],"need":[156],"add":[158],"parameters":[159],"network,":[163],"reduces":[165,252],"computation":[167,203],"To":[171],"address":[172],"complex":[176],"structures":[178],"lead":[181],"slower":[183],"detection,":[184],"spatial":[186],"pyramid":[187],"pooling":[188],"replaced":[194],"focal":[196],"modulation":[197],"networks,":[198],"greatly":[200],"simplifies":[201],"process.":[204],"The":[205,227],"experimental":[206],"validation":[207],"was":[208],"carried":[209],"out":[210],"on":[211],"scrap":[213],"steel":[214],"dataset":[215],"containing":[216],"large":[218],"number":[219],"targets":[221],"multiple":[223],"shapes":[224],"sizes.":[226],"results":[228],"showed":[229],"improved":[232],"AP":[238],"(average":[239],"precision)":[240],"by":[241,249,258],"2.1%,":[242],"mAP":[244],"(mean":[245],"average":[246],"precision":[247],"value)":[248],"0.8%,":[250],"FPS":[254],"(frames":[255],"per":[256],"second)":[257],"5.4,":[259],"meets":[261],"performance":[263],"requirements":[264],"real-time":[266],"industrial":[267],"inspection.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-03T08:47:05.690250","created_date":"2025-10-10T00:00:00"}
