{"id":"https://openalex.org/W4416250279","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227372","title":"High-Precision Fabric Defect Detection via Adaptive Shape Convolutions and Large Kernel Spatial Modeling","display_name":"High-Precision Fabric Defect Detection via Adaptive Shape Convolutions and Large Kernel Spatial Modeling","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250279","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227372"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061209735","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0003-0801-0417"},"institutions":[{"id":"https://openalex.org/I4210150411","display_name":"Shandong Youth University of Political Science","ror":"https://ror.org/04bwp4t29","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210150411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["Shandong Youth University of Political Science,School of Information Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Youth University of Political Science,School of Information Engineering,Jinan,China","institution_ids":["https://openalex.org/I4210150411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102018871","display_name":"Yang Xu","orcid":"https://orcid.org/0000-0003-3335-3278"},"institutions":[{"id":"https://openalex.org/I4210150411","display_name":"Shandong Youth University of Political Science","ror":"https://ror.org/04bwp4t29","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210150411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Xu","raw_affiliation_strings":["Shandong Youth University of Political Science,School of Information Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Youth University of Political Science,School of Information Engineering,Jinan,China","institution_ids":["https://openalex.org/I4210150411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101263846","display_name":"Zheng Hui","orcid":"https://orcid.org/0009-0006-7342-2142"},"institutions":[{"id":"https://openalex.org/I4210150411","display_name":"Shandong Youth University of Political Science","ror":"https://ror.org/04bwp4t29","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210150411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zheng","raw_affiliation_strings":["Shandong Youth University of Political Science,School of Information Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Youth University of Political Science,School of Information Engineering,Jinan,China","institution_ids":["https://openalex.org/I4210150411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054854467","display_name":"Baotian Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150411","display_name":"Shandong Youth University of Political Science","ror":"https://ror.org/04bwp4t29","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210150411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baotian Li","raw_affiliation_strings":["Shandong Youth University of Political Science,School of Information Engineering,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Youth University of Political Science,School of Information Engineering,Jinan,China","institution_ids":["https://openalex.org/I4210150411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210150411"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8550999760627747,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8550999760627747,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0982000008225441,"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/T11595","display_name":"Textile materials and evaluations","score":0.004699999932199717,"subfield":{"id":"https://openalex.org/subfields/2507","display_name":"Polymers and Plastics"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7307000160217285},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6848000288009644},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5209000110626221},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.498199999332428},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49140000343322754},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4839000105857849},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4731000065803528}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7480000257492065},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7307000160217285},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6848000288009644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5382000207901001},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.498199999332428},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4839000105857849},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4731000065803528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31709998846054077},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3010999858379364},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29019999504089355},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2655999958515167}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227372","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W3099927511","https://openalex.org/W3100813167","https://openalex.org/W3194043088","https://openalex.org/W4212872446","https://openalex.org/W4214507171","https://openalex.org/W4249839590","https://openalex.org/W4284664266","https://openalex.org/W4285300999","https://openalex.org/W4289943791","https://openalex.org/W4308866570","https://openalex.org/W4312403909","https://openalex.org/W4316660753","https://openalex.org/W4317513057","https://openalex.org/W4366310361","https://openalex.org/W4382278196","https://openalex.org/W4384818140","https://openalex.org/W4386377137","https://openalex.org/W4387451053","https://openalex.org/W4390190894","https://openalex.org/W4390231633","https://openalex.org/W4391041864","https://openalex.org/W4393139826","https://openalex.org/W4396594834","https://openalex.org/W4398176426","https://openalex.org/W4399302436","https://openalex.org/W4400969859","https://openalex.org/W4401122175","https://openalex.org/W4401126708","https://openalex.org/W4402351971","https://openalex.org/W4409366412","https://openalex.org/W4409367143","https://openalex.org/W4413147621","https://openalex.org/W4415798884"],"related_works":[],"abstract_inverted_index":{"Detecting":[0],"fabric":[1,52,138],"defects":[2],"in":[3,36,149],"the":[4,13,58,67,79,90,93,99,113,130,136,152],"textile":[5],"industry":[6],"remains":[7],"a":[8,146],"challenging":[9],"task":[10],"due":[11],"to":[12,81,107,157],"diverse":[14],"and":[15,31,85,97,126,161],"complex":[16],"nature":[17],"of":[18,92],"defect":[19,53,139],"patterns.":[20],"Traditional":[21],"methods":[22],"often":[23],"suffer":[24],"from":[25],"slow":[26],"inference":[27],"speeds,":[28],"limited":[29],"accuracy,":[30],"inadequate":[32],"recognition":[33],"rates,":[34],"particularly":[35],"scenarios":[37],"involving":[38],"intricate":[39],"or":[40],"subtle":[41],"defects.":[42],"To":[43],"overcome":[44],"these":[45],"limitations,":[46],"we":[47],"introduce":[48],"Fab-ASLKS,":[49],"an":[50],"advanced":[51],"detection":[54,140],"framework":[55],"built":[56],"upon":[57],"YOLOv8s":[59],"architecture.":[60],"Fab-ASLKS":[61,144],"incorporates":[62],"two":[63],"key":[64],"modules:":[65],"(1)":[66],"Adaptive":[68],"Shape":[69],"Convolution":[70,103],"Module":[71,104],"(ASCM),":[72],"which":[73],"leverages":[74],"adaptive":[75],"shape":[76],"convolution":[77],"within":[78,112],"Neck":[80],"enhance":[82],"feature":[83,124],"fusion":[84],"improve":[86],"efficiency":[87],"by":[88],"extending":[89],"capabilities":[91],"standard":[94],"C2f":[95],"structure,":[96],"(2)":[98],"Large":[100],"Kernel":[101],"Shift":[102],"(LKSCM),":[105],"designed":[106],"emulate":[108],"large":[109],"kernel":[110],"effects":[111],"Backbone,":[114],"enabling":[115],"superior":[116],"spatial":[117],"information":[118,127],"extraction.":[119],"These":[120],"modules":[121],"collaboratively":[122],"optimize":[123],"extraction":[125],"integration":[128],"across":[129],"network.":[131],"Extensive":[132],"experiments":[133],"conducted":[134],"on":[135],"Tianchi":[137],"dataset":[141],"demonstrate":[142],"that":[143],"achieves":[145],"5%":[147],"improvement":[148],"mAP@50":[150],"over":[151],"baseline,":[153],"showcasing":[154],"its":[155],"capability":[156],"deliver":[158],"high":[159],"precision":[160],"efficiency.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}