{"id":"https://openalex.org/W2791709739","doi":"https://doi.org/10.1109/tim.2018.2795178","title":"An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces","display_name":"An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces","publication_year":2018,"publication_date":"2018-02-05","ids":{"openalex":"https://openalex.org/W2791709739","doi":"https://doi.org/10.1109/tim.2018.2795178","mag":"2791709739"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2018.2795178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2018.2795178","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","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/A5103208729","display_name":"Shuang Mei","orcid":null},"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":"Shuang Mei","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004324946","display_name":"Hua Yang","orcid":"https://orcid.org/0000-0002-5430-5630"},"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":"Hua Yang","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-5430-5630","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053892414","display_name":"Zhouping Yin","orcid":"https://orcid.org/0000-0001-5766-2337"},"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":"Zhouping Yin","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":23.9823,"has_fulltext":false,"cited_by_count":306,"citation_normalized_percentile":{"value":0.99557919,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"67","issue":"6","first_page":"1266","last_page":"1277"},"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.992900013923645,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.754280686378479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6936655044555664},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6854623556137085},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5531387329101562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5437144637107849},{"id":"https://openalex.org/keywords/visual-inspection","display_name":"Visual inspection","score":0.5389050245285034},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46841540932655334},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4640810489654541},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4568842053413391},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41684186458587646},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3103436231613159},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22279492020606995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14530819654464722}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.754280686378479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6936655044555664},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6854623556137085},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5531387329101562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5437144637107849},{"id":"https://openalex.org/C168820333","wikidata":"https://www.wikidata.org/wiki/Q448889","display_name":"Visual inspection","level":2,"score":0.5389050245285034},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46841540932655334},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4640810489654541},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4568842053413391},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41684186458587646},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3103436231613159},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22279492020606995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14530819654464722},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2018.2795178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2018.2795178","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G2840902503","display_name":null,"funder_award_id":"51475193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7298260633","display_name":null,"funder_award_id":"51327801","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W2574642","https://openalex.org/W49146665","https://openalex.org/W211198884","https://openalex.org/W1005811612","https://openalex.org/W1806891645","https://openalex.org/W1976606301","https://openalex.org/W1982245376","https://openalex.org/W1988299413","https://openalex.org/W1988963939","https://openalex.org/W2002259470","https://openalex.org/W2006551019","https://openalex.org/W2021158839","https://openalex.org/W2026445526","https://openalex.org/W2048632148","https://openalex.org/W2053757129","https://openalex.org/W2056597368","https://openalex.org/W2080896707","https://openalex.org/W2082265779","https://openalex.org/W2084314862","https://openalex.org/W2088478449","https://openalex.org/W2096653978","https://openalex.org/W2097946161","https://openalex.org/W2101234009","https://openalex.org/W2111815479","https://openalex.org/W2113101204","https://openalex.org/W2117312310","https://openalex.org/W2118328928","https://openalex.org/W2122374500","https://openalex.org/W2130258210","https://openalex.org/W2133013766","https://openalex.org/W2134258345","https://openalex.org/W2141200610","https://openalex.org/W2145094598","https://openalex.org/W2146292423","https://openalex.org/W2147950119","https://openalex.org/W2159479423","https://openalex.org/W2295362590","https://openalex.org/W2344428106","https://openalex.org/W2384495648","https://openalex.org/W2418691539","https://openalex.org/W2468676150","https://openalex.org/W2501700740","https://openalex.org/W2520363778","https://openalex.org/W2545941211","https://openalex.org/W2568595749","https://openalex.org/W2589306531","https://openalex.org/W2997574889","https://openalex.org/W3005347330","https://openalex.org/W4250664506","https://openalex.org/W4301872509","https://openalex.org/W4393805319","https://openalex.org/W6600096878","https://openalex.org/W6675354045","https://openalex.org/W6681096077","https://openalex.org/W6697616483","https://openalex.org/W6733893350"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2909431601","https://openalex.org/W4294770367"],"abstract_inverted_index":{"Automated":[0],"defect":[1,88,120,177],"inspection":[2,105,121,137,178],"has":[3,110],"long":[4],"been":[5],"a":[6],"challenging":[7],"task":[8],"especially":[9],"in":[10,96,122,144],"industrial":[11],"applications,":[12],"where":[13],"collecting":[14],"and":[15,25,36,65,90,162,176,191,202,210],"labeling":[16],"large":[17],"amounts":[18],"of":[19,76,118,158,164,204],"defective":[20],"samples":[21,42],"are":[22,80,180,195],"usually":[23],"harsh":[24],"impracticable.":[26],"In":[27],"this":[28,145,169],"paper,":[29],"we":[30],"propose":[31],"an":[32],"approach":[33,47],"to":[34,101,147],"detect":[35],"localize":[37],"defects":[38],"with":[39,55,185],"only":[40],"defect-free":[41],"for":[43,85],"model":[44],"training.":[45],"This":[46,107,154],"is":[48,99,126,133,142,156],"carried":[49],"out":[50],"by":[51],"reconstructing":[52],"image":[53],"patches":[54,79],"convolutional":[56],"denoising":[57],"autoencoder":[58],"networks":[59],"at":[60],"different":[61,71],"Gaussian":[62],"pyramid":[63,152],"levels,":[64],"synthesizing":[66],"detection":[67],"results":[68,149,198],"from":[69,150],"these":[70],"resolution":[72],"channels.":[73],"Reconstruction":[74],"residuals":[75],"the":[77,83,91,103,116,136,160,165,200,205],"training":[78],"used":[81],"as":[82],"indicator":[84],"direct":[86],"pixelwise":[87],"prediction,":[89],"reconstruction":[92],"residual":[93],"map":[94],"generated":[95],"each":[97],"channel":[98],"combined":[100],"generate":[102],"final":[104],"result.":[106],"novel":[108],"method":[109,146,207],"two":[111],"prominent":[112],"characteristics,":[113],"which":[114],"benefit":[115],"implementation":[117],"automatic":[119],"practice.":[123],"First,":[124],"it":[125],"absolutely":[127],"unsupervised":[128],"that":[129],"no":[130],"human":[131],"intervention":[132],"needed":[134],"throughout":[135],"process.":[138],"Second,":[139],"multimodal":[140],"strategy":[141,155],"utilized":[143],"synthesize":[148],"multiple":[151],"levels.":[153],"capable":[157],"improving":[159],"robustness":[161],"accuracy":[163,179],"method.":[166],"To":[167],"evaluate":[168],"approach,":[170],"experiments":[171],"on":[172,189,208],"convergence,":[173],"noise":[174],"immunity,":[175],"conducted.":[181],"Furthermore,":[182],"comparative":[183],"tests":[184],"some":[186],"excellent":[187],"algorithms":[188],"actual":[190],"simulated":[192],"data":[193],"sets":[194],"performed.":[196],"Experimental":[197],"demonstrated":[199],"effectiveness":[201],"superiority":[203],"proposed":[206],"homogeneous":[209],"nonregular":[211],"textured":[212],"surfaces.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":41},{"year":2024,"cited_by_count":36},{"year":2023,"cited_by_count":60},{"year":2022,"cited_by_count":63},{"year":2021,"cited_by_count":44},{"year":2020,"cited_by_count":38},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}