{"id":"https://openalex.org/W3010725630","doi":"https://doi.org/10.1117/12.2540464","title":"Defective samples simulation through neural style transfer for automatic surface defect segment","display_name":"Defective samples simulation through neural style transfer for automatic surface defect segment","publication_year":2020,"publication_date":"2020-03-12","ids":{"openalex":"https://openalex.org/W3010725630","doi":"https://doi.org/10.1117/12.2540464","mag":"3010725630"},"language":"en","primary_location":{"id":"doi:10.1117/12.2540464","doi":"https://doi.org/10.1117/12.2540464","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2540464","pdf_url":null,"source":{"id":"https://openalex.org/S7407087523","display_name":"International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems (OIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.03334","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102007758","display_name":"Taoran Wei","orcid":"https://orcid.org/0000-0001-7741-8286","observed_orcids":["https://orcid.org/0000-0001-7741-8286"]},"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":"Taoran Wei","raw_affiliation_strings":["Huazhong Univ. of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Univ. of Science and Technology (China)","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026988178","display_name":"Danhua Cao","orcid":"https://orcid.org/0009-0000-6196-2332","observed_orcids":["https://orcid.org/0009-0000-6196-2332"]},"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":"Danhua Cao","raw_affiliation_strings":["Huazhong Univ. of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Univ. of Science and Technology (China)","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075223758","display_name":"Xingru Jiang","orcid":null,"observed_orcids":[]},"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":"Xingru Jiang","raw_affiliation_strings":["Huazhong Univ. of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Univ. of Science and Technology (China)","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034832362","display_name":"Caiyun Zheng","orcid":null,"observed_orcids":[]},"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":"Caiyun Zheng","raw_affiliation_strings":["Huazhong Univ. of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Univ. of Science and Technology (China)","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085696768","display_name":"Lizhe Liu","orcid":"https://orcid.org/0000-0001-5111-0750","observed_orcids":["https://orcid.org/0000-0001-5111-0750"]},"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":"Lizhe Liu","raw_affiliation_strings":["Huazhong Univ. of Science and Technology (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong Univ. of Science and Technology (China)","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":2.2339,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86692759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"6"},"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":0.9990000128746033,"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":0.9990000128746033,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0003000000142492354,"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"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/surface-defect-segmentation","display_name":"surface defect segmentation","score":0.8939999938011169},{"id":"https://openalex.org/keywords/neural-style-transfer","display_name":"neural style transfer","score":0.9879999756813049},{"id":"https://openalex.org/keywords/color-consistency","display_name":"color consistency","score":0.7440000176429749},{"id":"https://openalex.org/keywords/texture-consistency","display_name":"texture consistency","score":0.8149999976158142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7797728776931763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7310049533843994},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6621882915496826},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6456133723258972},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6430397033691406},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6385427713394165},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5136744379997253},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4803827404975891},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47437435388565063},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.45898425579071045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45641544461250305},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44842296838760376},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4412781894207001},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.429410457611084},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39463603496551514},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2190345823764801},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08057907223701477},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1117/12.2540464","doi":"https://doi.org/10.1117/12.2540464","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2540464","pdf_url":null,"source":{"id":"https://openalex.org/S7407087523","display_name":"International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems (OIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.03334","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.03334","pdf_url":"https://arxiv.org/pdf/1910.03334","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1910.03334","doi":"https://doi.org/10.48550/arxiv.1910.03334","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.03334","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.03334","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.03334","pdf_url":"https://arxiv.org/pdf/1910.03334","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3010725630.pdf","grobid_xml":"https://content.openalex.org/works/W3010725630.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1910657905","https://openalex.org/W1923697677","https://openalex.org/W2034856412","https://openalex.org/W2103559027","https://openalex.org/W2124351162","https://openalex.org/W2331128040","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2475287302","https://openalex.org/W2502312327","https://openalex.org/W2557615495","https://openalex.org/W2560023338","https://openalex.org/W2585235684","https://openalex.org/W2630837129","https://openalex.org/W2898545436","https://openalex.org/W2899771611","https://openalex.org/W2899983521","https://openalex.org/W2905416267","https://openalex.org/W2920946673","https://openalex.org/W2944279536","https://openalex.org/W2949650786","https://openalex.org/W2952232639","https://openalex.org/W2962793481","https://openalex.org/W2964121744","https://openalex.org/W2964309882"],"related_works":["https://openalex.org/W3040458218","https://openalex.org/W4226403630","https://openalex.org/W2954860285","https://openalex.org/W4409416933","https://openalex.org/W4415250252","https://openalex.org/W4395010363","https://openalex.org/W7131076986","https://openalex.org/W7160596656","https://openalex.org/W4399207715","https://openalex.org/W7164733920"],"abstract_inverted_index":{"Owing":[0],"to":[1,16,70,98,116,134],"the":[2,75,79,84,88,93,100,104,107,113,119,122,145,149,154,160,167,171,176,186],"lack":[3],"of":[4,45,74,121,131,170],"defect":[5,28,46,140,151],"samples":[6,47,55,152,157,179],"in":[7],"industrial":[8],"product":[9],"quality":[10,120],"inspection,":[11],"trained":[12,173],"segmentation":[13,58,141],"model":[14,172],"tends":[15],"overfit":[17],"when":[18],"applied":[19],"online.":[20],"To":[21,82],"address":[22],"this":[23],"problem,":[24],"we":[25,63,91,110,126],"propose":[26,127],"a":[27,42,65,128],"sample":[29,188],"simulation":[30,38,54,156,178],"algorithm":[31,39,97],"based":[32],"on":[33,159],"neural":[34],"style":[35,95],"transfer.":[36],"The":[37,163],"requires":[40],"only":[41,175],"small":[43],"number":[44],"for":[48,56,139],"training,":[49],"and":[50,78,153],"can":[51],"efficiently":[52],"generate":[53],"next-step":[57],"task.":[59,142],"In":[60],"our":[61],"work,":[62],"introduce":[64],"masked":[66],"histogram":[67,114],"matching":[68],"module":[69],"maintain":[71],"color":[72],"consistency":[73,86],"generated":[76,101,123,155,177],"area":[77,102],"true":[80],"defect.":[81],"preserve":[83],"texture":[85],"with":[87,148,174],"surrounding":[89],"pixels,":[90],"take":[92],"fast":[94],"transfer":[96],"blend":[99],"into":[103],"background.":[105],"At":[106],"same":[108],"time,":[109],"also":[111],"use":[112],"loss":[115],"further":[117],"improve":[118],"image.":[124],"Besides,":[125],"novel":[129],"structure":[130],"segment":[132,146],"net":[133,147],"make":[135],"it":[136],"more":[137],"suitable":[138],"We":[143],"train":[144],"real":[150,187],"separately":[158],"button":[161],"datasets.":[162],"results":[164],"show":[165],"that":[166],"F1":[168],"score":[169],"reaches":[180],"0.80,":[181],"which":[182],"is":[183],"better":[184],"than":[185],"result.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2020-03-23T00:00:00"}