{"id":"https://openalex.org/W3094374092","doi":"https://doi.org/10.1109/tim.2020.3026801","title":"Deep Learning-Based Generic Automatic Surface Defect Inspection (ASDI) With Pixelwise Segmentation","display_name":"Deep Learning-Based Generic Automatic Surface Defect Inspection (ASDI) With Pixelwise Segmentation","publication_year":2020,"publication_date":"2020-10-16","ids":{"openalex":"https://openalex.org/W3094374092","doi":"https://doi.org/10.1109/tim.2020.3026801","mag":"3094374092"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3026801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3026801","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/A5026068874","display_name":"Xiaojun Wu","orcid":"https://orcid.org/0000-0003-4988-5420"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojun Wu","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-4988-5420","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036054001","display_name":"Lingteng Qiu","orcid":"https://orcid.org/0000-0002-3250-0486"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"LingTeng Qiu","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3250-0486","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052772478","display_name":"Xiaodong Gu","orcid":"https://orcid.org/0000-0003-2623-7973"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Gu","raw_affiliation_strings":["Alibaba AILab, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2623-7973","affiliations":[{"raw_affiliation_string":"Alibaba AILab, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107746585","display_name":"Zhili Long","orcid":"https://orcid.org/0000-0002-6404-1982"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhili Long","raw_affiliation_strings":["School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-6404-1982","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2425,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.95707055,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"10"},"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":0.9955999851226807,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7324744462966919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7035737037658691},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7007554173469543},{"id":"https://openalex.org/keywords/subnetwork","display_name":"Subnetwork","score":0.6681615114212036},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6069430708885193},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5896410942077637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5604732632637024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5572448968887329},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5294047594070435},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.46098265051841736},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.42905810475349426},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4204671382904053},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41024351119995117},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38672274351119995},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33996328711509705},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11524805426597595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7324744462966919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7035737037658691},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7007554173469543},{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.6681615114212036},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6069430708885193},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5896410942077637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5604732632637024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5572448968887329},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5294047594070435},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.46098265051841736},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.42905810475349426},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4204671382904053},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41024351119995117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38672274351119995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33996328711509705},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11524805426597595},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"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:10.1109/tim.2020.3026801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3026801","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":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G2585986280","display_name":null,"funder_award_id":"2020B090926001","funder_id":"https://openalex.org/F4320336405","funder_display_name":"Special Project for Research and Development in Key areas of Guangdong Province"},{"id":"https://openalex.org/G3980671298","display_name":null,"funder_award_id":"U1713206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G505651778","display_name":null,"funder_award_id":"U1913215","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"},{"id":"https://openalex.org/F4320336405","display_name":"Special Project for Research and Development in Key areas of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1575677815","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1986306729","https://openalex.org/W2052545764","https://openalex.org/W2097946161","https://openalex.org/W2099471712","https://openalex.org/W2109255472","https://openalex.org/W2194775991","https://openalex.org/W2404464147","https://openalex.org/W2412782625","https://openalex.org/W2418934460","https://openalex.org/W2585635281","https://openalex.org/W2630837129","https://openalex.org/W2739748921","https://openalex.org/W2762457108","https://openalex.org/W2772386856","https://openalex.org/W2884195426","https://openalex.org/W2890747436","https://openalex.org/W2891336752","https://openalex.org/W2899242765","https://openalex.org/W2912729634","https://openalex.org/W2923486253","https://openalex.org/W2962879692","https://openalex.org/W2963016543","https://openalex.org/W2963150697","https://openalex.org/W2963849369","https://openalex.org/W2963857746","https://openalex.org/W2964121744","https://openalex.org/W2964309882","https://openalex.org/W2997148427","https://openalex.org/W3008725296","https://openalex.org/W3104156061","https://openalex.org/W3106250896","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6634296514","https://openalex.org/W6639102338","https://openalex.org/W6639824700","https://openalex.org/W6735913928","https://openalex.org/W6739696289","https://openalex.org/W6741832134","https://openalex.org/W6748481559","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758","https://openalex.org/W2993564273","https://openalex.org/W4286907753"],"abstract_inverted_index":{"Automatic":[0],"surface":[1,30,111],"defect":[2,84,112,212],"inspection":[3,90],"(ASDI)":[4],"is":[5,42,76,140,160,193],"a":[6,36,51,68,77,124,131,136,250],"crucial":[7],"and":[8,18,118,135,175,199,224,230,260],"challenging":[9,119],"problem":[10],"in":[11,44,103,221],"industry":[12],"because":[13],"it":[14],"affects":[15],"the":[16,59,82,88,100,104,143,152,164,168,171,177,183,187,191,246,272,276],"quality":[17],"efficiency":[19],"of":[20,130,145,167,180,190,242,252,279],"production":[21],"greatly.":[22],"Deep":[23],"learning-based":[24],"methods":[25],"achieve":[26,208],"promising":[27],"improvements":[28],"for":[29,142,148,263],"detection,":[31],"but":[32],"they":[33],"rely":[34],"on":[35,58,211,245],"massive":[37],"training":[38,62],"data":[39,63,85,91,101,113,226,274],"set":[40],"that":[41,54,75,108,128,202],"impractical":[43],"industry.":[45],"In":[46,151,182],"this":[47],"study,":[48],"we":[49,66],"propose":[50],"generic":[52],"method":[53],"works":[55],"effectively":[56],"even":[57],"small":[60],"size":[61],"set.":[64],"Especially,":[65],"introduce":[67],"ResMask":[69],"generative":[70],"adversarial":[71],"network":[72,192],"(GAN)":[73],"framework":[74],"residual":[78],"GAN":[79],"to":[80,97,162,234],"expand":[81],"insufficient":[83],"sets.":[86],"Meanwhile,":[87],"existing":[89],"sets":[92,102,114,227],"are":[93,121],"so":[94],"much":[95],"easier":[96],"detect":[98],"than":[99],"real":[105],"industrial":[106,110],"scenarios":[107],"new":[109],"containing":[115],"more":[116],"diverse":[117],"images":[120,248],"established.":[122],"Then,":[123],"coarse-to-fine":[125],"module":[126],"(CFM)":[127],"consists":[129],"coarse":[132,153],"detection":[133,147,154,173,277],"subnetwork":[134,139],"fine":[137,184],"segmentation":[138,185],"proposed":[141],"needs":[144],"fast":[146],"high-resolution":[149],"images.":[150,270],"stage,":[155,186],"spatial":[156],"pyramid":[157],"pooling":[158],"(SPP)":[159],"utilized":[161],"increase":[163],"receptive":[165,188],"field":[166,189],"network,":[169],"reduce":[170],"false":[172],"rate,":[174],"determine":[176],"approximate":[178],"location":[179],"defects.":[181],"enlarged":[194],"by":[195],"atrous":[196],"SPP":[197],"(ASPP),":[198],"skip":[200],"links":[201],"incorporate":[203],"low-level":[204],"with":[205,249],"high-level":[206],"features":[207],"pixelwise":[209],"precision":[210],"segmentation.":[213],"Finally,":[214],"our":[215],"algorithm":[216],"has":[217],"achieved":[218],"state-of-the-art":[219],"results":[220],"DAGM,":[222],"HR,":[223],"WB":[225],"(0.859,":[228],"0.761,":[229],"0.805,":[231],"respectively)":[232],"according":[233],"MIoU.":[235],"It":[236],"achieves":[237],"an":[238],"average":[239],"processing":[240],"time":[241],"44.4":[243],"ms":[244,262],"test":[247],"resolution":[251],"<inline-formula>":[253,264],"<tex-math":[254,265],"notation=\"LaTeX\">$512":[255],"\\,\\,\\times":[256],"\\,\\,":[257],"512$":[258],"</tex-math></inline-formula>":[259,269],"131.6":[261],"notation=\"LaTeX\">$2048":[266],"\\times":[267],"2048$":[268],"On":[271],"DAGM":[273],"set,":[275],"accuracy":[278],"mean":[280],"intersection":[281],"over":[282],"union":[283],"(MIoU)":[284],"reaches":[285],"0.859.":[286]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
