{"id":"https://openalex.org/W3000423400","doi":"https://doi.org/10.1109/sensors43011.2019.8956629","title":"Coarse-to-Fine Adaptive Illumination Hard-Adjustment for Vision Inspection System Under Uncertain Imaging Conditions","display_name":"Coarse-to-Fine Adaptive Illumination Hard-Adjustment for Vision Inspection System Under Uncertain Imaging Conditions","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3000423400","doi":"https://doi.org/10.1109/sensors43011.2019.8956629","mag":"3000423400"},"language":"en","primary_location":{"id":"doi:10.1109/sensors43011.2019.8956629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sensors43011.2019.8956629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE SENSORS","raw_type":"proceedings-article"},"type":"conference-paper","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/A5025080900","display_name":"Fei Chang","orcid":"https://orcid.org/0000-0002-7655-6350"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Chang","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070416597","display_name":"Yunqiang Duan","orcid":"https://orcid.org/0000-0002-2901-7135"},"institutions":[{"id":"https://openalex.org/I4210087772","display_name":"National Computer Network Emergency Response Technical Team/Coordination Center of Chinar","ror":"https://ror.org/00247dh76","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210087772"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunqiang Duan","raw_affiliation_strings":["Coordination Center of China (CNCERT/CC),National Computer network Emergency Response technical Team,China","National Computer network Emergency Response technical Team, Coordination Center of China (CNCERT/CC), China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Coordination Center of China (CNCERT/CC),National Computer network Emergency Response technical Team,China","institution_ids":["https://openalex.org/I4210087772"]},{"raw_affiliation_string":"National Computer network Emergency Response technical Team, Coordination Center of China (CNCERT/CC), China","institution_ids":["https://openalex.org/I4210087772"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343911","display_name":"Min Liu","orcid":"https://orcid.org/0000-0002-7273-0518"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Liu","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102897652","display_name":"Mingyu Dong","orcid":"https://orcid.org/0000-0003-3625-2296"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyu Dong","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China","Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.27297457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9984999895095825,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9976999759674072,"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/computer-vision","display_name":"Computer vision","score":0.8122528791427612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7653382420539856},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193397283554077},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.6388669610023499},{"id":"https://openalex.org/keywords/factory","display_name":"Factory (object-oriented programming)","score":0.6324129700660706},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5426135659217834},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.5097062587738037},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.485522985458374},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.42743757367134094},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4259242117404938},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3139774203300476},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.22060173749923706}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8122528791427612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7653382420539856},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193397283554077},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.6388669610023499},{"id":"https://openalex.org/C40149104","wikidata":"https://www.wikidata.org/wiki/Q5620977","display_name":"Factory (object-oriented programming)","level":2,"score":0.6324129700660706},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5426135659217834},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.5097062587738037},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.485522985458374},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.42743757367134094},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4259242117404938},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3139774203300476},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.22060173749923706},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sensors43011.2019.8956629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sensors43011.2019.8956629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE SENSORS","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1973650920","https://openalex.org/W2163170350","https://openalex.org/W2174794239","https://openalex.org/W2254039850","https://openalex.org/W2471988522","https://openalex.org/W2783399029","https://openalex.org/W2794543249","https://openalex.org/W2884367402","https://openalex.org/W2890715498","https://openalex.org/W2893707916","https://openalex.org/W2919115771","https://openalex.org/W2930700974","https://openalex.org/W2952523420","https://openalex.org/W4293584584","https://openalex.org/W6750227808","https://openalex.org/W6754632766"],"related_works":["https://openalex.org/W2385368906","https://openalex.org/W2902924992","https://openalex.org/W2626642044","https://openalex.org/W2619807045","https://openalex.org/W2388758053","https://openalex.org/W93537448","https://openalex.org/W2949734191","https://openalex.org/W2017333877","https://openalex.org/W2048332520","https://openalex.org/W2566290947"],"abstract_inverted_index":{"High-quality":[0],"image":[1,38,62],"acquisition":[2,63],"under":[3,152],"uncertain":[4,66,153],"imaging":[5,27,67,154],"conditions":[6],"(such":[7],"as":[8,47,142],"uneven":[9],"and":[10,15,87,96,119],"varied":[11],"illuminations,":[12],"various":[13],"viewpoints":[14],"different":[16],"object":[17,88],"distances,":[18],"etc.)":[19],"is":[20,34,75],"a":[21,69,105,133],"very":[22],"challenging":[23,43],"task.":[24],"However,":[25],"the":[26,59,79,99,128,135],"quality":[28],"of":[29,51,61,84,113,121],"industrial":[30,130,148],"vision":[31,149],"inspection":[32,50,101,150],"system":[33,102,151],"vital":[35],"to":[36,57,65,77,98],"subsequent":[37],"processing,":[39],"especially":[40],"for":[41,109,147],"those":[42],"detection":[44,112],"tasks,":[45],"such":[46],"tiny":[48,110],"defect":[49,111],"paint":[52,114],"car-body":[53,115],"surfaces.":[54,116],"In":[55],"order":[56],"overcome":[58],"challenge":[60],"due":[64],"conditions,":[68],"two-stage":[70],"adaptive":[71,144],"illumination":[72],"adjustment":[73],"method":[74,123],"proposed":[76,136],"handle":[78],"uncertainty":[80],"caused":[81],"by":[82,127],"diversities":[83],"lighting,":[85],"viewpoint":[86],"distance.":[89],"Our":[90],"algorithm":[91],"framework":[92,138],"has":[93,124],"been":[94,125],"implemented":[95],"applied":[97],"mobile":[100],"deployed":[103],"in":[104],"car":[106],"painting":[107],"factory":[108],"The":[117],"efficiency":[118],"effectiveness":[120],"our":[122],"validated":[126],"actual":[129],"application.":[131],"As":[132],"result,":[134],"coarse-to-fine":[137],"can":[139],"be":[140],"viewed":[141],"an":[143],"hard-adjustment":[145],"solution":[146],"conditions.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
