{"id":"https://openalex.org/W4402263870","doi":"https://doi.org/10.1109/tim.2024.3415785","title":"Clustering Federated Learning for Wafer Defects Classification on Statistical Heterogeneous Data","display_name":"Clustering Federated Learning for Wafer Defects Classification on Statistical Heterogeneous Data","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402263870","doi":"https://doi.org/10.1109/tim.2024.3415785"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3415785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3415785","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011969885","display_name":"Guang Yang","orcid":"https://orcid.org/0000-0002-2100-7493"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Yang","raw_affiliation_strings":["State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-2100-7493","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030868537","display_name":"Zhijia Yang","orcid":"https://orcid.org/0000-0002-8664-440X"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijia Yang","raw_affiliation_strings":["State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-8664-440X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012220391","display_name":"Shuping Cui","orcid":"https://orcid.org/0000-0001-6843-2174"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuping Cui","raw_affiliation_strings":["Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-6843-2174","affiliations":[{"raw_affiliation_string":"Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043075442","display_name":"Chunhe Song","orcid":"https://orcid.org/0000-0001-8392-1777"},"institutions":[{"id":"https://openalex.org/I142078773","display_name":"Shenyang Institute of Automation","ror":"https://ror.org/00ft6nj33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I142078773","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhe Song","raw_affiliation_strings":["State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-8392-1777","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Robotics, Shenyang Institute of Automation, and the Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I142078773","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058975702","display_name":"Jizhou Wang","orcid":"https://orcid.org/0009-0003-3421-4808"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jizhou Wang","raw_affiliation_strings":["KINGSEMI Company Ltd., Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0003-3421-4808","affiliations":[{"raw_affiliation_string":"KINGSEMI Company Ltd., Shenyang, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074237395","display_name":"Haodong Wei","orcid":"https://orcid.org/0009-0001-0955-2237"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haodong Wei","raw_affiliation_strings":["KINGSEMI Company Ltd., Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0001-0955-2237","affiliations":[{"raw_affiliation_string":"KINGSEMI Company Ltd., Shenyang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9701,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87397756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"13"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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":0.984000027179718,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7595235109329224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6380559802055359},{"id":"https://openalex.org/keywords/wafer","display_name":"Wafer","score":0.626798152923584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48502177000045776},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43358609080314636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43302732706069946},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2957266569137573},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.21266669034957886},{"id":"https://openalex.org/keywords/optoelectronics","display_name":"Optoelectronics","score":0.12294194102287292}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7595235109329224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380559802055359},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.626798152923584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48502177000045776},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43358609080314636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43302732706069946},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2957266569137573},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.21266669034957886},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.12294194102287292}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2024.3415785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3415785","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2020286945","https://openalex.org/W2103205252","https://openalex.org/W2286515324","https://openalex.org/W2535838896","https://openalex.org/W2593609447","https://openalex.org/W2767053056","https://openalex.org/W2790607928","https://openalex.org/W2798589477","https://openalex.org/W2807006176","https://openalex.org/W2920311927","https://openalex.org/W2922187519","https://openalex.org/W2945987769","https://openalex.org/W2997583607","https://openalex.org/W3080934299","https://openalex.org/W3082906739","https://openalex.org/W3092686161","https://openalex.org/W3101748915","https://openalex.org/W3123899295","https://openalex.org/W3196371845","https://openalex.org/W3199144655","https://openalex.org/W3213815372","https://openalex.org/W4210508597","https://openalex.org/W4210547660","https://openalex.org/W4210605464","https://openalex.org/W4214914131","https://openalex.org/W4226322519","https://openalex.org/W4285260612","https://openalex.org/W4297687186","https://openalex.org/W4312699393","https://openalex.org/W4378697021","https://openalex.org/W4385643643","https://openalex.org/W6752029299","https://openalex.org/W6759238902","https://openalex.org/W6773817997","https://openalex.org/W6779269186","https://openalex.org/W6790034021","https://openalex.org/W6791305734","https://openalex.org/W6795843344","https://openalex.org/W6796484261"],"related_works":["https://openalex.org/W1998662473","https://openalex.org/W2075391483","https://openalex.org/W2742348144","https://openalex.org/W2038820605","https://openalex.org/W1985417357","https://openalex.org/W2115053376","https://openalex.org/W2367528910","https://openalex.org/W1991489478","https://openalex.org/W2121416564","https://openalex.org/W2129617696"],"abstract_inverted_index":{"Data-driven":[0],"deep":[1,40],"learning":[2,41,48],"techniques":[3],"for":[4,134,186],"wafer":[5,10,30,61,89],"defect":[6,22],"image":[7,85],"classification":[8],"provide":[9,166],"manufacturers":[11,72],"with":[12,123,202,252],"a":[13,28,50,119,167,183,193,241,253],"tool":[14],"to":[15,35,75,79,100,209],"rapidly":[16],"identify":[17],"surface":[18],"defects.":[19],"However,":[20],"the":[21,37,54,67,126,141,146,162,172,187,198,207,211,218,247],"data":[23,55,69,204,230],"and":[24,56,84,111],"computational":[25,57],"capabilities":[26,58],"of":[27,39,59,145,174,200,213,220],"single":[29],"manufacturer":[31],"are":[32],"often":[33],"insufficient":[34],"support":[36],"training":[38],"models.":[42],"In":[43,125],"response,":[44],"we":[45,117,129,165],"introduce":[46],"federated":[47,250],"(FL),":[49],"paradigm":[51],"that":[52,66,171,236],"leverages":[53],"various":[60,229],"manufacturers,":[62],"all":[63],"while":[64,151],"ensuring":[65],"original":[68],"from":[70],"different":[71,93,96],"remain":[73],"unexposed":[74],"each":[76,135,157],"other.":[77],"Due":[78],"variations":[80],"in":[81,95],"manufacturing":[82,97],"processes":[83],"acquisition":[86],"equipment,":[87],"identical":[88],"defects":[90],"can":[91,106,239],"exhibit":[92],"features":[94,205],"settings,":[98],"leading":[99],"statistically":[101],"heterogeneous":[102],"datasets.":[103],"This":[104],"heterogeneity":[105,231],"reduce":[107],"model":[108,222],"convergence":[109,255],"speed":[110],"accuracy.":[112],"To":[113],"counteract":[114],"this":[115],"issue,":[116],"propose":[118],"personalized":[120],"FL":[121],"approach":[122],"clustering.":[124],"personalization":[127],"phase,":[128,164],"train":[130],"distinct":[131],"network":[132],"layers":[133],"client\u2019s":[136,158],"local":[137],"model,":[138],"capitalizing":[139],"on":[140,156],"feature":[142],"extraction":[143],"capability":[144],"global":[147,221],"model\u2019s":[148],"shallow":[149],"network,":[150],"also":[152],"achieving":[153],"commendable":[154],"performance":[155],"unique":[159],"dataset.":[160],"During":[161],"clustering":[163,188,195,199],"theoretical":[168,184],"analysis,":[169],"demonstrating":[170],"divergence":[173],"weights":[175],"between":[176],"two":[177],"models":[178],"is":[179],"bounded":[180],"above,":[181],"laying":[182],"foundation":[185],"operation.":[189],"We":[190,224],"then":[191],"enhance":[192],"density-based":[194],"method,":[196],"enabling":[197],"clients":[201],"similar":[203],"without":[206],"need":[208],"specify":[210],"number":[212],"cluster":[214],"centers,":[215],"thus":[216],"mitigating":[217],"problem":[219],"oscillation.":[223],"have":[225],"conducted":[226],"experiments":[227,234],"under":[228],"scenarios.":[232],"The":[233],"show":[235],"our":[237],"method":[238],"achieve":[240],"2.8%":[242],"accuracy":[243],"improvement":[244],"average":[245],"versus":[246],"compared":[248],"state-of-the-art":[249],"methods":[251],"faster":[254],"rate.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
