{"id":"https://openalex.org/W4394794221","doi":"https://doi.org/10.1007/s10845-024-02372-9","title":"Visual coating inspection framework via self-labeling and multi-stage deep learning strategies","display_name":"Visual coating inspection framework via self-labeling and multi-stage deep learning strategies","publication_year":2024,"publication_date":"2024-04-14","ids":{"openalex":"https://openalex.org/W4394794221","doi":"https://doi.org/10.1007/s10845-024-02372-9"},"language":"en","primary_location":{"id":"doi:10.1007/s10845-024-02372-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02372-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02372-9.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02372-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111047094","display_name":"Changheon Han","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Changheon Han","raw_affiliation_strings":["School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100685128","display_name":"Jiho Lee","orcid":"https://orcid.org/0000-0003-3096-9261"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiho Lee","raw_affiliation_strings":["School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018569736","display_name":"Martin Byung\u2010Guk Jun","orcid":"https://orcid.org/0000-0002-0512-7209"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin B. G. Jun","raw_affiliation_strings":["Indiana Manufacturing Competitiveness Center (IN-MaC), Purdue University, West Lafayette, IN, 47906, USA","School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA"],"affiliations":[{"raw_affiliation_string":"Indiana Manufacturing Competitiveness Center (IN-MaC), Purdue University, West Lafayette, IN, 47906, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47906, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444709","display_name":"Sang Won Lee","orcid":"https://orcid.org/0000-0002-6352-5635"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang Won Lee","raw_affiliation_strings":["School of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001272385","display_name":"Huitaek Yun","orcid":"https://orcid.org/0000-0002-4136-7947"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Huitaek Yun","raw_affiliation_strings":["Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001272385"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":2.0504,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.87159972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"36","issue":"4","first_page":"2461","last_page":"2478"},"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9912999868392944,"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/T12080","display_name":"Injection Molding Process and Properties","score":0.972100019454956,"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":0.6708784699440002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6514802575111389},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.624725341796875},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5242907404899597},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46874621510505676},{"id":"https://openalex.org/keywords/coating","display_name":"Coating","score":0.4523894488811493},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4346208870410919},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42218005657196045},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4116997718811035},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37364524602890015},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.12068438529968262}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6708784699440002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6514802575111389},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.624725341796875},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5242907404899597},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46874621510505676},{"id":"https://openalex.org/C2781448156","wikidata":"https://www.wikidata.org/wiki/Q1570182","display_name":"Coating","level":2,"score":0.4523894488811493},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4346208870410919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42218005657196045},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4116997718811035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37364524602890015},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.12068438529968262},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10845-024-02372-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02372-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02372-9.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:joinma:v:36:y:2025:i:4:d:10.1007_s10845-024-02372-9","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s10845-024-02372-9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":{"id":"doi:10.1007/s10845-024-02372-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02372-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02372-9.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2389861276","display_name":null,"funder_award_id":"20015060","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G6326951936","display_name":null,"funder_award_id":"AM-2125826","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6587702527","display_name":"Collaborative Research: Data-Driven Metrology and Inspection Technology for Semiconductor Wafer-Level Manufacturing","funder_award_id":"2125826","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8582691448","display_name":null,"funder_award_id":"MOTIE, Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G992484961","display_name":null,"funder_award_id":"Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320324161","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394794221.pdf"},"referenced_works_count":77,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1653130573","https://openalex.org/W1846645794","https://openalex.org/W1965696824","https://openalex.org/W1966520588","https://openalex.org/W1979754799","https://openalex.org/W2007203285","https://openalex.org/W2011674654","https://openalex.org/W2013500537","https://openalex.org/W2016221699","https://openalex.org/W2021966702","https://openalex.org/W2028045978","https://openalex.org/W2039885833","https://openalex.org/W2048322459","https://openalex.org/W2059432853","https://openalex.org/W2080964655","https://openalex.org/W2089468765","https://openalex.org/W2102605133","https://openalex.org/W2112796928","https://openalex.org/W2115940646","https://openalex.org/W2129270900","https://openalex.org/W2132186680","https://openalex.org/W2167801685","https://openalex.org/W2193145675","https://openalex.org/W2303099520","https://openalex.org/W2324369761","https://openalex.org/W2468676150","https://openalex.org/W2548865889","https://openalex.org/W2559655401","https://openalex.org/W2613718673","https://openalex.org/W2616247523","https://openalex.org/W2620915497","https://openalex.org/W2786672974","https://openalex.org/W2796325360","https://openalex.org/W2803544974","https://openalex.org/W2809136100","https://openalex.org/W2883908928","https://openalex.org/W2919115771","https://openalex.org/W2935842115","https://openalex.org/W2939398318","https://openalex.org/W2943425778","https://openalex.org/W2962949934","https://openalex.org/W2963037989","https://openalex.org/W2970971581","https://openalex.org/W2990138404","https://openalex.org/W2993018413","https://openalex.org/W2995523160","https://openalex.org/W2997183031","https://openalex.org/W3011698693","https://openalex.org/W3022506809","https://openalex.org/W3024889357","https://openalex.org/W3092207554","https://openalex.org/W3102564565","https://openalex.org/W3106250896","https://openalex.org/W3113276149","https://openalex.org/W3133076875","https://openalex.org/W3164104137","https://openalex.org/W3168997536","https://openalex.org/W3188836964","https://openalex.org/W3205224229","https://openalex.org/W3211268145","https://openalex.org/W3215680118","https://openalex.org/W4205843111","https://openalex.org/W4206914912","https://openalex.org/W4221141050","https://openalex.org/W4225818162","https://openalex.org/W4229021979","https://openalex.org/W4246020459","https://openalex.org/W4283448485","https://openalex.org/W4300011764","https://openalex.org/W4312220502","https://openalex.org/W4316661403","https://openalex.org/W4319869073","https://openalex.org/W4362722341","https://openalex.org/W4382317777","https://openalex.org/W4385580947","https://openalex.org/W6686375811"],"related_works":["https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Abstract":[0],"An":[1],"instantaneous":[2],"and":[3,17,39,112,121,141,152,166,221,242,265],"precise":[4],"coating":[5,124,175,193,210,232],"inspection":[6,32,99],"method":[7],"is":[8,157,204],"imperative":[9],"to":[10,56,103,172,206],"mitigate":[11],"the":[12,27,49,74,105,174,209,231,235,266,270,273],"risk":[13],"of":[14,29,238,247,272],"flaws,":[15],"defects,":[16],"discrepancies":[18],"on":[19,178,217],"coated":[20,140,179],"surfaces.":[21],"While":[22],"many":[23],"studies":[24],"have":[25],"demonstrated":[26,225],"effectiveness":[28],"automated":[30,97],"visual":[31,98],"(AVI)":[33,100],"approaches":[34,70],"enhanced":[35],"by":[36,73,137,159],"computer":[37],"vision":[38,53],"deep":[40,67,95],"learning,":[41,68],"critical":[42],"challenges":[43],"exist":[44],"for":[45,62,76,107],"practical":[46],"applications":[47],"in":[48,84,116,229],"manufacturing":[50],"domain.":[51],"Computer":[52],"has":[54],"proven":[55],"be":[57],"inflexible,":[58],"demanding":[59],"sophisticated":[60],"algorithms":[61],"diverse":[63],"feature":[64,109],"extraction.":[65],"In":[66],"supervised":[69],"are":[71],"constrained":[72],"need":[75],"annotated":[77,187],"datasets,":[78],"whereas":[79],"unsupervised":[80],"methods":[81],"often":[82],"result":[83],"lower":[85],"performance.":[86],"Addressing":[87],"these":[88,191],"challenges,":[89],"this":[90],"paper":[91],"proposes":[92],"a":[93,197,245],"novel":[94],"learning-based":[96],"framework":[101,130,224],"designed":[102],"minimize":[104],"necessity":[106],"extensive":[108],"engineering,":[110],"programming,":[111],"manual":[113],"data":[114],"annotation":[115],"classifying":[117],"fuel":[118],"injection":[119],"nozzles":[120,143],"discerning":[122],"their":[123],"interfaces":[125,233],"from":[126,163,190],"scratch.":[127],"This":[128,156,223],"proposed":[129],"comprises":[131],"six":[132],"integral":[133],"components:":[134],"It":[135],"begins":[136],"distinguishing":[138],"between":[139],"uncoated":[142,164],"through":[144],"gray":[145],"level":[146],"co-occurrence":[147],"matrix":[148],"(GLCM)-based":[149],"texture":[150],"analysis":[151],"autoencoder":[153],"(AE)-based":[154],"classification.":[155],"followed":[158],"cropping":[160],"surface":[161],"images":[162,249],"nozzles,":[165],"then":[167],"building":[168],"an":[169],"AE":[170],"model":[171,203,219],"estimate":[173],"interface":[176,194,211],"locations":[177],"nozzles.":[180],"The":[181,213],"next":[182],"step":[183],"involves":[184],"generating":[185],"autonomously":[186],"datasets":[188],"derived":[189],"estimated":[192],"locations.":[195,212],"Subsequently,":[196],"convolutional":[198],"neural":[199],"network":[200],"(CNN)-based":[201],"detection":[202],"trained":[205],"accurately":[207],"localize":[208],"final":[214],"component":[215],"focuses":[216],"enhancing":[218],"performance":[220],"trustworthiness.":[222],"over":[226],"95%":[227],"accuracy":[228],"pinpointing":[230],"within":[234],"error":[236],"range":[237],"\u00b1":[239],"6":[240],"pixels":[241],"processed":[243],"at":[244],"rate":[246],"7.18":[248],"per":[250],"second.":[251],"Additionally,":[252],"explainable":[253],"artificial":[254],"intelligence":[255],"(XAI)":[256],"techniques":[257],"such":[258],"as":[259],"t-distributed":[260],"stochastic":[261],"neighbor":[262],"embedding":[263],"(t-SNE)":[264],"integrated":[267],"gradient":[268],"substantiated":[269],"reliability":[271],"models.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}