{"id":"https://openalex.org/W4388821419","doi":"https://doi.org/10.1109/apsipaasc58517.2023.10317264","title":"Application of Wafer Defect Pattern Classification Model in the Semiconductor Industry","display_name":"Application of Wafer Defect Pattern Classification Model in the Semiconductor Industry","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388821419","doi":"https://doi.org/10.1109/apsipaasc58517.2023.10317264"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc58517.2023.10317264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc58517.2023.10317264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5039368747","display_name":"Chin\u2010Wei Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I185940356","display_name":"Soochow University","ror":"https://ror.org/05kvm7n82","country_code":"TW","type":"education","lineage":["https://openalex.org/I185940356"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Wei Lee","raw_affiliation_strings":["Soochow University,Taiwan","Soochow University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Taiwan","institution_ids":["https://openalex.org/I185940356"]},{"raw_affiliation_string":"Soochow University, Taiwan","institution_ids":["https://openalex.org/I185940356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080567273","display_name":"Daniel Hl\u00e1dek","orcid":"https://orcid.org/0000-0003-1148-3194"},"institutions":[{"id":"https://openalex.org/I183764125","display_name":"Technical University of Ko\u0161ice","ror":"https://ror.org/05xm08015","country_code":"SK","type":"education","lineage":["https://openalex.org/I183764125"]}],"countries":["SK"],"is_corresponding":false,"raw_author_name":"Daniel Hl\u00e1dek","raw_affiliation_strings":["Technical University in Ko&#x0161;ice,Slovakia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University in Ko&#x0161;ice,Slovakia","institution_ids":["https://openalex.org/I183764125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022501326","display_name":"Mat\u00fa\u0161 Pleva","orcid":"https://orcid.org/0000-0003-4380-0801"},"institutions":[{"id":"https://openalex.org/I183764125","display_name":"Technical University of Ko\u0161ice","ror":"https://ror.org/05xm08015","country_code":"SK","type":"education","lineage":["https://openalex.org/I183764125"]}],"countries":["SK"],"is_corresponding":false,"raw_author_name":"Mat\u00fa\u0161 Pleva","raw_affiliation_strings":["Technical University in Ko&#x0161;ice,Slovakia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University in Ko&#x0161;ice,Slovakia","institution_ids":["https://openalex.org/I183764125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082271172","display_name":"Yuan\u2010Fu Liao","orcid":"https://orcid.org/0000-0003-0191-2178"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yuan-Fu Liao","raw_affiliation_strings":["National Yang Ming Chiao Tung University,HsinChu,Taiwan","National Yang Ming Chiao Tung University, HsinChu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,HsinChu,Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"National Yang Ming Chiao Tung University, HsinChu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091093449","display_name":"Ming-Hsiang Su","orcid":"https://orcid.org/0000-0003-0633-774X"},"institutions":[{"id":"https://openalex.org/I185940356","display_name":"Soochow University","ror":"https://ror.org/05kvm7n82","country_code":"TW","type":"education","lineage":["https://openalex.org/I185940356"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ming-Hsiang Su","raw_affiliation_strings":["Soochow University,Taiwan","Soochow University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow University,Taiwan","institution_ids":["https://openalex.org/I185940356"]},{"raw_affiliation_string":"Soochow University, Taiwan","institution_ids":["https://openalex.org/I185940356"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0481,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76583759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2173","last_page":"2177"},"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":0.9972000122070312,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9749000072479248,"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":0.708324670791626},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6887199878692627},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6705595850944519},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5794808268547058},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5150079727172852},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4922243654727936},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4848281145095825},{"id":"https://openalex.org/keywords/semiconductor-device-fabrication","display_name":"Semiconductor device fabrication","score":0.46745285391807556},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.4624955654144287},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4284389019012451},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.42022523283958435},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41714489459991455},{"id":"https://openalex.org/keywords/wafer","display_name":"Wafer","score":0.34946078062057495},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19101330637931824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.708324670791626},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6887199878692627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6705595850944519},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5794808268547058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5150079727172852},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4922243654727936},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4848281145095825},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.46745285391807556},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.4624955654144287},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4284389019012451},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.42022523283958435},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41714489459991455},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.34946078062057495},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19101330637931824},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc58517.2023.10317264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc58517.2023.10317264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1564419782","https://openalex.org/W1979091955","https://openalex.org/W2020286945","https://openalex.org/W2028501442","https://openalex.org/W2088252378","https://openalex.org/W2499581503","https://openalex.org/W2565516711","https://openalex.org/W2789876780","https://openalex.org/W2792944472","https://openalex.org/W2942208503","https://openalex.org/W3005641657","https://openalex.org/W3017210109","https://openalex.org/W3023211159","https://openalex.org/W3148181069","https://openalex.org/W4210430458","https://openalex.org/W4235298171","https://openalex.org/W4241699496","https://openalex.org/W4243634040","https://openalex.org/W4252813286","https://openalex.org/W4293581782","https://openalex.org/W4376271539","https://openalex.org/W6632865047","https://openalex.org/W6797083918"],"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/W2955207210","https://openalex.org/W2115053376","https://openalex.org/W2367528910","https://openalex.org/W2992897358","https://openalex.org/W2631724279"],"abstract_inverted_index":{"Deep":[0],"learning":[1,61],"(DL)":[2],"methods":[3],"are":[4],"widely":[5],"employed":[6],"in":[7,83,114],"the":[8,25,29,35,42,66,84,100,116,120],"semiconductor":[9],"manufacturing":[10],"process":[11],"to":[12,64,77,93],"enhance":[13,65],"pattern":[14],"recognition":[15],"and":[16,59,80,89,123],"classification":[17,26,68,121],"accuracy,":[18],"specifically":[19],"for":[20],"addressing":[21],"defect":[22,39],"patterns.":[23],"However,":[24],"performance":[27],"of":[28,38,73,108,118],"current":[30],"models":[31],"is":[32,76],"hindered":[33],"by":[34],"imbalanced":[36],"distribution":[37],"data":[40,57],"within":[41],"test":[43],"dataset.":[44],"To":[45],"tackle":[46],"this":[47,49,74],"issue,":[48],"study":[50,75],"presents":[51],"a":[52],"feature":[53],"extraction":[54],"approach":[55],"utilizing":[56],"transformation,":[58],"ensemble":[60],"techniques":[62],"aiming":[63],"model's":[67],"performance.":[69],"The":[70,96],"primary":[71],"objective":[72],"mitigate":[78],"selection":[79],"imbalance":[81],"problems":[82],"dataset":[85],"through":[86],"random":[87],"sampling":[88],"assigning":[90],"distinct":[91],"weights":[92],"individual":[94],"classifiers.":[95],"results":[97],"demonstrate":[98],"that":[99],"proposed":[101],"method":[102],"achieves":[103],"an":[104],"impressive":[105],"accuracy":[106],"rate":[107],"95.09%,":[109],"thus":[110],"substantiating":[111],"its":[112],"efficacy":[113],"improving":[115],"robustness":[117],"both":[119],"model":[122],"wafer":[124],"classification.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
