{"id":"https://openalex.org/W4386547127","doi":"https://doi.org/10.3390/s23187755","title":"PCB Defect Detection via Local Detail and Global Dependency Information","display_name":"PCB Defect Detection via Local Detail and Global Dependency Information","publication_year":2023,"publication_date":"2023-09-08","ids":{"openalex":"https://openalex.org/W4386547127","doi":"https://doi.org/10.3390/s23187755","pmid":"https://pubmed.ncbi.nlm.nih.gov/37765814"},"language":"en","primary_location":{"id":"doi:10.3390/s23187755","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187755","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7755/pdf?version=1694165978","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/18/7755/pdf?version=1694165978","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077666707","display_name":"Boqian Feng","orcid":"https://orcid.org/0000-0001-6954-694X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bixian Feng","raw_affiliation_strings":["Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi\u2019an 710071, China","Xidian University, Xi\u2019an 710126, China","Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi'an 710071, China"],"raw_orcid":"https://orcid.org/0000-0001-6954-694X","affiliations":[{"raw_affiliation_string":"Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi\u2019an 710126, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101425172","display_name":"Jueping Cai","orcid":"https://orcid.org/0000-0002-1852-0982"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jueping Cai","raw_affiliation_strings":["Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi\u2019an 710071, China","Xidian University, Xi\u2019an 710126, China","Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi'an 710071, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi\u2019an 710071, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi\u2019an 710126, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Wide Band Gap Semiconductor Technology State Key Laboratory, Xidian University, Xi'an 710071, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101425172"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":3.6862,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.93028836,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"18","first_page":"7755","last_page":"7755"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.6159594655036926},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6067671775817871},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.551217257976532},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.460889995098114},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4518040716648102},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4324411451816559},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3718445301055908},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3641173243522644},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33121249079704285},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2194114625453949},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.13870078325271606},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1039271354675293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6159594655036926},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6067671775817871},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.551217257976532},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.460889995098114},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4518040716648102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4324411451816559},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3718445301055908},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3641173243522644},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33121249079704285},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2194114625453949},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.13870078325271606},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1039271354675293},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23187755","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187755","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7755/pdf?version=1694165978","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37765814","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37765814","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10538067","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10538067","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10538067/pdf/sensors-23-07755.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:803324405e7d48e1bd3592bdc6dec7b5","is_oa":true,"landing_page_url":"https://doaj.org/article/803324405e7d48e1bd3592bdc6dec7b5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 18, p 7755 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/18/7755/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23187755","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23187755","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23187755","pdf_url":"https://www.mdpi.com/1424-8220/23/18/7755/pdf?version=1694165978","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G8615985595","display_name":null,"funder_award_id":"62274123","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"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4386547127.pdf"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1836465849","https://openalex.org/W1986587559","https://openalex.org/W2079387956","https://openalex.org/W2112796928","https://openalex.org/W2132346196","https://openalex.org/W2156387975","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2747355315","https://openalex.org/W2884561390","https://openalex.org/W2941001797","https://openalex.org/W2963037989","https://openalex.org/W2964241181","https://openalex.org/W3106250896","https://openalex.org/W3138516171","https://openalex.org/W3186516637","https://openalex.org/W3195442750","https://openalex.org/W4200118103","https://openalex.org/W4292972665","https://openalex.org/W4303981225","https://openalex.org/W4320717537","https://openalex.org/W4321460455","https://openalex.org/W4362496246","https://openalex.org/W4375869048","https://openalex.org/W4385453033","https://openalex.org/W4386066092","https://openalex.org/W4388284323","https://openalex.org/W6682889407","https://openalex.org/W6842051710"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W3124914020","https://openalex.org/W2141033859","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W4391621807","https://openalex.org/W2156434174","https://openalex.org/W2990636717"],"abstract_inverted_index":{"Due":[0],"to":[1,119,139,164,173,183,225],"the":[2,5,14,29,50,110,114,132,148,151,162,174,194,210,215,227,233,239],"impact":[3],"of":[4,16,53,150,229,243],"production":[6,47,55],"environment,":[7],"there":[8],"may":[9],"be":[10],"quality":[11],"issues":[12],"on":[13,58,166,193],"surface":[15,36],"printed":[17],"circuit":[18],"boards":[19],"(PCBs),":[20],"which":[21,100],"could":[22],"result":[23],"in":[24,77,169],"significant":[25],"economic":[26],"losses":[27],"during":[28],"application":[30],"process.":[31],"As":[32],"a":[33,74,90],"result,":[34],"PCB":[35,46,54],"defect":[37,92,186],"detection":[38,93,187],"has":[39],"become":[40],"an":[41],"essential":[42],"step":[43],"for":[44],"managing":[45],"quality.":[48],"With":[49],"continuous":[51],"advancement":[52],"technology,":[56],"defects":[57],"PCBs":[59],"now":[60],"exhibit":[61],"characteristics":[62],"such":[63],"as":[64],"small":[65,80],"areas":[66],"and":[67,81,106,127,143,156,181,196,213,241],"diverse":[68],"styles.":[69],"Utilizing":[70],"global":[71,128],"information":[72,124,130],"plays":[73],"crucial":[75],"role":[76],"detecting":[78],"these":[79],"variable":[82],"defects.":[83],"To":[84],"address":[85],"this":[86],"challenge,":[87],"we":[88,112,153,176,208],"propose":[89],"novel":[91],"framework":[94,203],"named":[95],"Defect":[96],"Detection":[97],"TRansformer":[98],"(DDTR),":[99],"combines":[101],"convolutional":[102],"neural":[103],"networks":[104],"(CNNs)":[105],"transformer":[107],"architectures.":[108],"In":[109],"backbone,":[111],"employ":[113,177],"Residual":[115],"Swin":[116,133],"Transformer":[117],"(ResSwinT)":[118],"extract":[120],"both":[121],"local":[122],"detail":[123],"using":[125],"ResNet":[126],"dependency":[129],"through":[131],"Transformer.":[134],"This":[135],"approach":[136],"allows":[137],"us":[138],"capture":[140],"multi-scale":[141],"features":[142,168],"enhance":[144],"feature":[145],"expression":[146],"capabilities.In":[147],"neck":[149],"network,":[152],"introduce":[154],"spatial":[155],"channel":[157],"multi-head":[158],"self-attention":[159],"(SCSA),":[160],"enabling":[161],"network":[163],"focus":[165],"advantageous":[167],"different":[170],"dimensions.":[171],"Moving":[172],"head,":[175],"multiple":[178],"cascaded":[179],"detectors":[180],"classifiers":[182],"further":[184],"improve":[185],"accuracy.":[188],"We":[189],"conducted":[190],"extensive":[191],"experiments":[192,222,237],"PKU-Market-PCB":[195],"DeepPCB":[197],"datasets.":[198],"Comparing":[199],"our":[200,244],"proposed":[201],"DDTR":[202,234],"with":[204],"existing":[205],"common":[206],"methods,":[207],"achieved":[209],"highest":[211],"F1-score":[212],"produced":[214],"most":[216],"informative":[217],"visualization":[218],"results.":[219],"Lastly,":[220],"ablation":[221],"were":[223],"performed":[224],"demonstrate":[226],"feasibility":[228],"individual":[230],"modules":[231],"within":[232],"framework.":[235],"These":[236],"confirmed":[238],"effectiveness":[240],"contributions":[242],"approach.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
