{"id":"https://openalex.org/W4376852406","doi":"https://doi.org/10.1145/3573942.3574107","title":"An Incremental Surface Defect Detection Method by Fused Unsupervised and Supervised Methods","display_name":"An Incremental Surface Defect Detection Method by Fused Unsupervised and Supervised Methods","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852406","doi":"https://doi.org/10.1145/3573942.3574107"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3574107","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3574107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","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/A5037211132","display_name":"Wanyu Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wanyu Deng","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-9818-5562","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001426366","display_name":"W Wang","orcid":"https://orcid.org/0000-0002-7149-8948"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-7149-8948","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006427506","display_name":"Jiahao Jie","orcid":"https://orcid.org/0000-0003-2172-6639"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Jie","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-2172-6639","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004315237","display_name":"Dunhai Wu","orcid":"https://orcid.org/0000-0002-6228-3806"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dunhai Wu","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-6228-3806","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037211132"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30971717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"867","last_page":"872"},"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":0.9889000058174133,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9865999817848206,"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/autoencoder","display_name":"Autoencoder","score":0.8632421493530273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8389948606491089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6918477416038513},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6597488522529602},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.6449416875839233},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6213405728340149},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5473740696907043},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4934510290622711},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.448835551738739},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4356829822063446},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4225141704082489},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4115346074104309},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.184538334608078},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16680431365966797},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1211504340171814}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8632421493530273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8389948606491089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6918477416038513},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6597488522529602},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.6449416875839233},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6213405728340149},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5473740696907043},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4934510290622711},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.448835551738739},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4356829822063446},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4225141704082489},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4115346074104309},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.184538334608078},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16680431365966797},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1211504340171814},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3574107","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3574107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.550000011920929,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2562062856","https://openalex.org/W2791709739","https://openalex.org/W2948982773","https://openalex.org/W3048633961","https://openalex.org/W3121084473","https://openalex.org/W6600013530","https://openalex.org/W6600160247","https://openalex.org/W6814992557"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W4220926404","https://openalex.org/W2806873178","https://openalex.org/W3123344745","https://openalex.org/W2770818364","https://openalex.org/W2965146396","https://openalex.org/W3148060700"],"abstract_inverted_index":{"Surface":[0],"defect":[1,27,44,73,140,146],"detection":[2,39,74],"is":[3,11,47,121,169,182],"an":[4,16],"essential":[5],"procedure":[6],"during":[7],"industrial":[8,53],"production.":[9],"It":[10],"a":[12,70,93,152,178],"challenge":[13],"to":[14,49,82,97,108,123,142,144,159,172,184],"establish":[15],"effective":[17],"model":[18],"for":[19,37,113],"the":[20,52,99,103,110,114,128,132,138,145,160,163,186,196],"surface":[21,72,86],"defects":[22,125],"inspection":[23,201],"of":[24,43,135,166],"products.":[25],"Because":[26],"samples":[28],"are":[29],"few":[30],"and":[31,79,137,188],"varied.":[32],"Current":[33],"supervised":[34,78,104,189],"learning":[35],"methods":[36],"object":[38],"require":[40],"large":[41],"amounts":[42],"data,":[45],"which":[46],"difficult":[48],"collect":[50],"in":[51],"scene.":[54],"The":[55,191],"unsupervised":[56,80,89,187],"method":[57,75,198],"based":[58],"on":[59],"image":[60,130,134,165],"reconstruction":[61],"often":[62],"reconstructs":[63],"defects.":[64,87],"In":[65],"this":[66],"paper,":[67],"we":[68],"propose":[69],"novel":[71,118],"by":[76,126,150],"fused":[77],"approaches":[81],"accurately":[83],"inspect":[84,109],"various":[85],"For":[88,102],"module,":[90,105],"it":[91],"employs":[92],"convolutional":[94],"autoencoder":[95],"(CAE)":[96],"reconstruct":[98],"defect-free":[100,161],"image.":[101,148],"use":[106],"CAE":[107,136],"defective":[111,115],"area":[112],"images.":[116],"A":[117],"loss":[119,180],"function":[120,181],"proposed":[122,197],"detect":[124],"making":[127],"residual":[129,164],"between":[131],"output":[133],"artificial":[139],"im":[141],"close":[143,171],"label":[147,154],"So,":[149],"adding":[151],"semantic":[153,175],"with":[155],"all":[156],"zero":[157],"values":[158],"image,":[162],"different":[167],"tasks":[168],"jointly":[170],"their":[173],"respective":[174],"labels.":[176],"Therefore,":[177],"unified":[179],"used":[183],"unify":[185],"methods.":[190],"experimental":[192],"results":[193],"show":[194],"that":[195],"achieves":[199],"better":[200],"accuracy.":[202]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}