{"id":"https://openalex.org/W4389428632","doi":"https://doi.org/10.1109/tim.2023.3338692","title":"A Novel Hierarchical Tree-DCNN Structure for Unbalanced Data Diagnosis in Microelectronic Manufacturing Process","display_name":"A Novel Hierarchical Tree-DCNN Structure for Unbalanced Data Diagnosis in Microelectronic Manufacturing Process","publication_year":2023,"publication_date":"2023-12-07","ids":{"openalex":"https://openalex.org/W4389428632","doi":"https://doi.org/10.1109/tim.2023.3338692"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3338692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3338692","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/A_novel_hierarchical_tree-DCNN_structure_for_unbalanced_data_diagnosis_in_microelectronic_manufacturing_process/24573319","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103073949","display_name":"Yong Zeng","orcid":"https://orcid.org/0000-0001-9399-3117"},"institutions":[{"id":"https://openalex.org/I4210122543","display_name":"Guangdong Polytechnic Normal University","ror":"https://ror.org/02pcb5m77","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zeng","raw_affiliation_strings":["School of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9399-3117","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I4210122543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057032580","display_name":"Yanfang Mei","orcid":"https://orcid.org/0000-0003-4990-6498"},"institutions":[{"id":"https://openalex.org/I4210122543","display_name":"Guangdong Polytechnic Normal University","ror":"https://ror.org/02pcb5m77","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfang Mei","raw_affiliation_strings":["School of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4990-6498","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I4210122543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101833098","display_name":"Yueming Hu","orcid":"https://orcid.org/0000-0003-3623-1188"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueming Hu","raw_affiliation_strings":["School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","Engineering Research Center for Precision Electronic Manufacturing Equipment, Ministry of Education and Guangdong Provincial Engineering Laboratory for Advanced Chip Intelligent Packaging Equipment, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3623-1188","affiliations":[{"raw_affiliation_string":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Engineering Research Center for Precision Electronic Manufacturing Equipment, Ministry of Education and Guangdong Provincial Engineering Laboratory for Advanced Chip Intelligent Packaging Equipment, Guangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082900845","display_name":"Zhengguo Sheng","orcid":"https://orcid.org/0000-0003-2143-4003"},"institutions":[{"id":"https://openalex.org/I162608824","display_name":"University of Sussex","ror":"https://ror.org/00ayhx656","country_code":"GB","type":"education","lineage":["https://openalex.org/I162608824"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhengguo Sheng","raw_affiliation_strings":["Department of Engineering and Design, University of Sussex, Brighton, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2143-4003","affiliations":[{"raw_affiliation_string":"Department of Engineering and Design, University of Sussex, Brighton, U.K","institution_ids":["https://openalex.org/I162608824"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3529,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67764402,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"11"},"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6350685954093933},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6133285760879517},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5986605286598206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5802851319313049},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5498834848403931},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5383682250976562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5045548677444458},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4636270999908447},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45491647720336914},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.320881187915802},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2536540627479553}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6350685954093933},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6133285760879517},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5986605286598206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5802851319313049},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5498834848403931},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5383682250976562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5045548677444458},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4636270999908447},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45491647720336914},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.320881187915802},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2536540627479553},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tim.2023.3338692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3338692","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/24573319","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_novel_hierarchical_tree-DCNN_structure_for_unbalanced_data_diagnosis_in_microelectronic_manufacturing_process/24573319","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/24573319","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/A_novel_hierarchical_tree-DCNN_structure_for_unbalanced_data_diagnosis_in_microelectronic_manufacturing_process/24573319","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G584279356","display_name":null,"funder_award_id":"61573146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6228941465","display_name":null,"funder_award_id":"2014ZX02503","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W955794068","https://openalex.org/W2027933820","https://openalex.org/W2036733754","https://openalex.org/W2052194651","https://openalex.org/W2080829704","https://openalex.org/W2125150158","https://openalex.org/W2141832011","https://openalex.org/W2153496385","https://openalex.org/W2241204461","https://openalex.org/W2338712801","https://openalex.org/W2592396164","https://openalex.org/W2622826443","https://openalex.org/W2795647708","https://openalex.org/W2886052255","https://openalex.org/W2895572611","https://openalex.org/W2898375427","https://openalex.org/W2940891324","https://openalex.org/W2963037989","https://openalex.org/W2968648382","https://openalex.org/W3122309346","https://openalex.org/W3127080232","https://openalex.org/W3127363706","https://openalex.org/W3176378302","https://openalex.org/W3204078905","https://openalex.org/W3217348973","https://openalex.org/W4205863267","https://openalex.org/W4312958416","https://openalex.org/W4377236653","https://openalex.org/W4379805117","https://openalex.org/W6677339812","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W2033512842","https://openalex.org/W4322734194","https://openalex.org/W1607054433","https://openalex.org/W3005535424","https://openalex.org/W4233600955","https://openalex.org/W2913665393","https://openalex.org/W2994319598","https://openalex.org/W2369695847","https://openalex.org/W2110842462"],"abstract_inverted_index":{"The":[0,140],"quality":[1,192],"of":[2,13,56,105,120,154,170,185],"flexible":[3],"integrated":[4],"circuit":[5],"substrates":[6],"(FICSs)":[7],"is":[8,73,111,123],"critical":[9],"to":[10,42,130,187],"the":[11,67,118,126,148,163,168],"reliability":[12],"various":[14,90],"electronic":[15],"products,":[16],"making":[17],"intelligent":[18],"defect":[19,32],"measurement":[20,173],"essential":[21,183],"for":[22,30,86,113],"efficient":[23],"manufacturing":[24],"and":[25,45,61,79,89,95,138,143,156,174,178],"cost-saving.":[26],"However,":[27],"existing":[28],"solutions":[29],"substrate":[31,171],"diagnosis":[33,82],"heavily":[34],"rely":[35],"on":[36,66,109,151],"human":[37],"visual":[38],"interpretation,":[39],"which":[40,180],"leads":[41],"poor":[43],"efficiency":[44],"a":[46,57,62,98,102,132],"high":[47,176],"error":[48],"rate.":[49],"A":[50],"novel":[51],"vision-based":[52],"detection":[53,136],"system":[54,165],"consisting":[55],"multiscale":[58],"imaging":[59],"module":[60],"hierarchical":[63,106],"structure":[64],"based":[65,108],"deep":[68],"convolution":[69],"neural":[70],"network":[71,127],"(DCNN)":[72],"proposed":[74,164],"in":[75,97,125],"this":[76],"article.":[77],"Rapid":[78],"accurate":[80],"fault":[81,115,172],"can":[83],"be":[84,93],"enabled":[85],"high-density":[87],"FICS,":[88],"defects":[91],"could":[92,166,181],"located":[94],"classified":[96],"coarse-to-fine":[99],"resolution.":[100],"Specifically,":[101],"new":[103],"mechanism":[104],"decision":[107],"DCNNs":[110],"built":[112],"FICS":[114,155,186],"diagnosis,":[116],"wherein":[117],"challenge":[119],"unbalanced":[121],"data":[122],"addressed":[124],"learning":[128],"process":[129],"reach":[131],"good":[133],"trade-off":[134],"between":[135],"accuracy":[137,177],"speed.":[139],"substantial":[141],"experiments":[142],"effectiveness":[144],"comparison":[145],"by":[146],"using":[147],"typical":[149],"methods":[150],"three":[152],"categories":[153],"their":[157],"corresponding":[158],"eight-type":[159],"faults":[160],"reveal":[161],"that":[162],"facilitate":[167],"solution":[169],"achieve":[175],"efficiency,":[179],"provide":[182],"information":[184],"divide":[188],"its":[189],"industrial":[190],"acceptance":[191],"level.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
