{"id":"https://openalex.org/W4388974804","doi":"https://doi.org/10.3390/s23239381","title":"Metal Surface Defect Detection Based on a Transformer with Multi-Scale Mask Feature Fusion","display_name":"Metal Surface Defect Detection Based on a Transformer with Multi-Scale Mask Feature Fusion","publication_year":2023,"publication_date":"2023-11-24","ids":{"openalex":"https://openalex.org/W4388974804","doi":"https://doi.org/10.3390/s23239381","pmid":"https://pubmed.ncbi.nlm.nih.gov/38067754"},"language":"en","primary_location":{"id":"doi:10.3390/s23239381","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239381","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9381/pdf?version=1700811924","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/1424-8220/23/23/9381/pdf?version=1700811924","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015503095","display_name":"Lin Zhao","orcid":"https://orcid.org/0009-0005-9601-5673"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Zhao","raw_affiliation_strings":["School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;"],"raw_orcid":"https://orcid.org/0009-0005-9601-5673","affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","institution_ids":["https://openalex.org/I51622183"]},{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;","institution_ids":["https://openalex.org/I51622183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101843137","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-4288-3345"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["School of Cyber Engineering, Xidian University, Xi\u2019an 710126, China","School of Cyber Engineering, Xidian University, Xi'an 710126, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Engineering, Xidian University, Xi\u2019an 710126, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Cyber Engineering, Xidian University, Xi'an 710126, China;","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054249230","display_name":"Tao Peng","orcid":"https://orcid.org/0000-0002-9425-2262"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Peng","raw_affiliation_strings":["School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","institution_ids":["https://openalex.org/I51622183"]},{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;","institution_ids":["https://openalex.org/I51622183"]}]},{"author_position":"last","author":{"id":null,"display_name":"Enrang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Enrang Zheng","raw_affiliation_strings":["School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China","institution_ids":["https://openalex.org/I51622183"]},{"raw_affiliation_string":"School of Electrical and Control Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China;","institution_ids":["https://openalex.org/I51622183"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51622183"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":2.1447,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.87630126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"23","first_page":"9381","last_page":"9381"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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":0.9810000061988831,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7265087962150574},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6521475315093994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6350653171539307},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5819604992866516},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5549578666687012},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4792911410331726},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4471549689769745},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4335877299308777},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43117856979370117},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4261319935321808},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3309710621833801},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15284445881843567},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08021503686904907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265087962150574},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6521475315093994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6350653171539307},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5819604992866516},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5549578666687012},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4792911410331726},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4471549689769745},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4335877299308777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43117856979370117},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4261319935321808},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3309710621833801},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15284445881843567},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08021503686904907},{"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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s23239381","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239381","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9381/pdf?version=1700811924","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:38067754","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38067754","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:10708611","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10708611","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10708611/pdf/sensors-23-09381.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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:e7ce078f4b1d429881554c85585755a8","is_oa":true,"landing_page_url":"https://doaj.org/article/e7ce078f4b1d429881554c85585755a8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 23, p 9381 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23239381","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23239381","pdf_url":"https://www.mdpi.com/1424-8220/23/23/9381/pdf?version=1700811924","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","score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G3431236262","display_name":null,"funder_award_id":"2021T140529","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4834066018","display_name":null,"funder_award_id":"ZYTS23170","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388974804.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1514907448","https://openalex.org/W2036705578","https://openalex.org/W2599354622","https://openalex.org/W2803446235","https://openalex.org/W2886479392","https://openalex.org/W2899280016","https://openalex.org/W2913074553","https://openalex.org/W2914570111","https://openalex.org/W2941813310","https://openalex.org/W2963045681","https://openalex.org/W2978971541","https://openalex.org/W3099658315","https://openalex.org/W3118600296","https://openalex.org/W3133719425","https://openalex.org/W3160074056","https://openalex.org/W3168124404","https://openalex.org/W3169651898","https://openalex.org/W3173538657","https://openalex.org/W3204520143","https://openalex.org/W3208797540","https://openalex.org/W3209793239","https://openalex.org/W4206947990","https://openalex.org/W4214694907","https://openalex.org/W4221140561","https://openalex.org/W4287887190","https://openalex.org/W4294651314","https://openalex.org/W4312290555","https://openalex.org/W4312772600","https://openalex.org/W4312849330","https://openalex.org/W4312910119","https://openalex.org/W4376607576","https://openalex.org/W4378714868","https://openalex.org/W4382317689","https://openalex.org/W4385801014","https://openalex.org/W4386047807","https://openalex.org/W4387682077","https://openalex.org/W6790908119","https://openalex.org/W6853228104"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2055243143","https://openalex.org/W4205302943","https://openalex.org/W4206178588","https://openalex.org/W4287635093","https://openalex.org/W3094491777","https://openalex.org/W3214715529"],"abstract_inverted_index":{"In":[0,59,172],"the":[1,8,23,26,81,89,101,104,109,112,157,161,165,169,178,187,201,207],"production":[2],"process":[3],"of":[4,12,25,40,42,141,164,180,209],"metal":[5,188,196],"industrial":[6,197],"products,":[7,28],"deficiencies":[9],"and":[10,15,72,108,130,135,183,200],"limitations":[11],"existing":[13],"technologies":[14],"working":[16],"conditions":[17],"can":[18,45],"have":[19],"adverse":[20],"effects":[21],"on":[22,67,177,186,194],"quality":[24],"final":[27],"making":[29],"surface":[30,50],"defect":[31,51],"detection":[32,52],"particularly":[33],"crucial.":[34],"However,":[35],"collecting":[36],"a":[37,54,64,68,94],"sufficient":[38],"number":[39],"samples":[41],"defective":[43],"products":[44],"be":[46],"challenging.":[47],"Therefore,":[48],"treating":[49],"as":[53],"semi-supervised":[55],"problem":[56],"is":[57],"appropriate.":[58],"this":[60,173],"paper,":[61,174],"we":[62,137,151,175],"propose":[63],"method":[65,79],"based":[66],"Transformer":[69,91],"with":[70,121],"pruned":[71],"merged":[73],"multi-scale":[74],"masked":[75],"feature":[76],"fusion.":[77],"This":[78],"learns":[80],"semantic":[82,147],"context":[83,148],"from":[84],"normal":[85],"samples.":[86],"We":[87,115,190],"incorporate":[88],"Vision":[90],"(ViT)":[92],"into":[93,156],"generative":[95],"adversarial":[96],"network":[97,120],"to":[98,125,144,159,205],"jointly":[99],"learn":[100],"generation":[102],"in":[103,111],"high-dimensional":[105],"image":[106],"space":[107],"inference":[110],"latent":[113],"space.":[114],"use":[116],"an":[117],"encoder-decoder":[118],"neural":[119],"long":[122],"skip":[123],"connections":[124],"capture":[126],"information":[127],"between":[128],"shallow":[129],"deep":[131],"layers.":[132],"During":[133],"training":[134,162,170],"testing,":[136],"design":[138],"block":[139],"masks":[140],"different":[142],"scales":[143],"obtain":[145],"rich":[146],"information.":[149],"Additionally,":[150],"introduce":[152],"token":[153],"merging":[154],"(ToMe)":[155],"ViT":[158],"improve":[160],"speed":[163],"model":[166],"without":[167],"affecting":[168],"results.":[171],"focus":[176],"problems":[179],"rust,":[181],"scratches,":[182],"other":[184],"defects":[185],"surface.":[189],"conduct":[191],"various":[192],"experiments":[193],"five":[195],"product":[198],"datasets":[199],"MVTec":[202],"AD":[203],"dataset":[204],"demonstrate":[206],"superiority":[208],"our":[210],"method.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
