{"id":"https://openalex.org/W4285410120","doi":"https://doi.org/10.1145/3532213.3532285","title":"Fabric Defect Defection based on Lightweight Convolutional Denoising Auto-Encoder","display_name":"Fabric Defect Defection based on Lightweight Convolutional Denoising Auto-Encoder","publication_year":2022,"publication_date":"2022-03-18","ids":{"openalex":"https://openalex.org/W4285410120","doi":"https://doi.org/10.1145/3532213.3532285"},"language":"en","primary_location":{"id":"doi:10.1145/3532213.3532285","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532213.3532285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-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/A5101980741","display_name":"Jin Dong","orcid":"https://orcid.org/0000-0003-4026-8338"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dong Jin","raw_affiliation_strings":["Huazhong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101412259","display_name":"Wenzheng Li","orcid":"https://orcid.org/0009-0008-4536-8948"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Li","raw_affiliation_strings":["Huazhong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075186257","display_name":"Zhigang Sun","orcid":"https://orcid.org/0009-0007-0434-4774"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Sun","raw_affiliation_strings":["Huazhong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101607875","display_name":"Xiao Li","orcid":"https://orcid.org/0000-0002-2583-4066"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Li","raw_affiliation_strings":["Huazhong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101980741"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11400465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"478","last_page":"483"},"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":1.0,"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":1.0,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9692999720573425,"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/bottleneck","display_name":"Bottleneck","score":0.7758685946464539},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7324608564376831},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6905665993690491},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6721717715263367},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5914306044578552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5592648983001709},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.498211145401001},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4951919615268707},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4840792715549469},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.42798054218292236},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4205988943576813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40411972999572754},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.32823267579078674},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16625672578811646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09063541889190674}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7758685946464539},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7324608564376831},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6905665993690491},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6721717715263367},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5914306044578552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5592648983001709},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.498211145401001},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4951919615268707},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4840792715549469},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.42798054218292236},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4205988943576813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40411972999572754},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.32823267579078674},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16625672578811646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09063541889190674},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3532213.3532285","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3532213.3532285","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W2122374500","https://openalex.org/W2131241448","https://openalex.org/W2133665775","https://openalex.org/W2145094598","https://openalex.org/W2321627895","https://openalex.org/W2791709739","https://openalex.org/W2809705434","https://openalex.org/W2941813310","https://openalex.org/W2951665052","https://openalex.org/W2963733773","https://openalex.org/W2982083293","https://openalex.org/W2997574889","https://openalex.org/W3037175147","https://openalex.org/W3083951643","https://openalex.org/W3110878409","https://openalex.org/W3201495614","https://openalex.org/W4376626035"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W1987128138","https://openalex.org/W2743976221"],"abstract_inverted_index":{"In":[0,27],"the":[1,5,11,78,87,100],"industrial":[2],"production":[3],"environment,":[4],"scarcity":[6],"of":[7,15],"defect":[8,17,29,63,104],"samples":[9,18],"and":[10,40,92,98],"high":[12,37],"labor":[13],"cost":[14,39],"labeling":[16],"make":[19],"supervised":[20],"machine":[21],"learning":[22,33],"models":[23,34],"difficult":[24],"to":[25,102],"implement.":[26],"addition,":[28],"detection":[30,64,105],"using":[31],"deep":[32],"usually":[35],"requires":[36],"computation":[38,97],"advanced":[41],"hardware":[42],"platform,":[43],"which":[44],"is":[45,75],"not":[46],"suitable":[47],"for":[48],"running":[49],"on":[50,67,106],"embedded":[51],"platforms.":[52,108],"To":[53],"solve":[54],"this":[55,57],"problem,":[56],"paper":[58],"proposes":[59],"an":[60],"unsupervised":[61],"fabric":[62],"method":[65,88],"based":[66],"lightweight":[68],"convolutional":[69],"denoising":[70],"auto-encoder(LCDAE).":[71],"The":[72],"LCDAE":[73],"model":[74],"constructed":[76],"by":[77],"bottleneck":[79],"layer":[80],"in":[81],"MobileNetV3.":[82],"Experimental":[83],"results":[84],"show":[85],"that":[86],"can":[89],"effectively":[90],"detect":[91],"localize":[93],"defects":[94],"with":[95],"less":[96],"has":[99],"potential":[101],"perform":[103],"edge-embedded":[107]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}