{"id":"https://openalex.org/W3032952423","doi":"https://doi.org/10.1109/vts48691.2020.9107570","title":"CNN-based Stochastic Regression for IDDQ Outlier Identification","display_name":"CNN-based Stochastic Regression for IDDQ Outlier Identification","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3032952423","doi":"https://doi.org/10.1109/vts48691.2020.9107570","mag":"3032952423"},"language":"en","primary_location":{"id":"doi:10.1109/vts48691.2020.9107570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts48691.2020.9107570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 38th VLSI Test Symposium (VTS)","raw_type":"proceedings-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/A5024940546","display_name":"Chun-Teng Chen","orcid":null},"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":true,"raw_author_name":"Chun-Teng Chen","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048521134","display_name":"Chia-Heng Yen","orcid":"https://orcid.org/0000-0002-6646-9253"},"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":"Chia-Heng Yen","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112899767","display_name":"Cheng-Yen Wen","orcid":null},"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":"Cheng-Yen Wen","raw_affiliation_strings":["Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101566595","display_name":"Chenghao Yang","orcid":"https://orcid.org/0000-0001-6242-7606"},"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":"Cheng-Hao Yang","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109999808","display_name":"Kai\u2013Chiang Wu","orcid":null},"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":"Kai-Chiang Wu","raw_affiliation_strings":["Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087280397","display_name":"Mason Chern","orcid":null},"institutions":[{"id":"https://openalex.org/I901624438","display_name":"Realtek (Taiwan)","ror":"https://ror.org/05x1ffr83","country_code":"TW","type":"company","lineage":["https://openalex.org/I901624438"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Mason Chern","raw_affiliation_strings":["Realtek Semiconductor Corporation, Taiwan"],"affiliations":[{"raw_affiliation_string":"Realtek Semiconductor Corporation, Taiwan","institution_ids":["https://openalex.org/I901624438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084399586","display_name":"Ying-Yen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I901624438","display_name":"Realtek (Taiwan)","ror":"https://ror.org/05x1ffr83","country_code":"TW","type":"company","lineage":["https://openalex.org/I901624438"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ying-Yen Chen","raw_affiliation_strings":["Realtek Semiconductor Corporation, Taiwan"],"affiliations":[{"raw_affiliation_string":"Realtek Semiconductor Corporation, Taiwan","institution_ids":["https://openalex.org/I901624438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102225158","display_name":"Chun\u2010Yi Kuo","orcid":null},"institutions":[{"id":"https://openalex.org/I901624438","display_name":"Realtek (Taiwan)","ror":"https://ror.org/05x1ffr83","country_code":"TW","type":"company","lineage":["https://openalex.org/I901624438"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Yi Kuo","raw_affiliation_strings":["Realtek Semiconductor Corporation, Taiwan"],"affiliations":[{"raw_affiliation_string":"Realtek Semiconductor Corporation, Taiwan","institution_ids":["https://openalex.org/I901624438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046781142","display_name":"Jih\u2010Nung Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I901624438","display_name":"Realtek (Taiwan)","ror":"https://ror.org/05x1ffr83","country_code":"TW","type":"company","lineage":["https://openalex.org/I901624438"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jih-Nung Lee","raw_affiliation_strings":["Realtek Semiconductor Corporation, Taiwan"],"affiliations":[{"raw_affiliation_string":"Realtek Semiconductor Corporation, Taiwan","institution_ids":["https://openalex.org/I901624438"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057687376","display_name":"Shu-Yi Kao","orcid":null},"institutions":[{"id":"https://openalex.org/I901624438","display_name":"Realtek (Taiwan)","ror":"https://ror.org/05x1ffr83","country_code":"TW","type":"company","lineage":["https://openalex.org/I901624438"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shu-Yi Kao","raw_affiliation_strings":["Realtek Semiconductor Corporation, Taiwan"],"affiliations":[{"raw_affiliation_string":"Realtek Semiconductor Corporation, Taiwan","institution_ids":["https://openalex.org/I901624438"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045156360","display_name":"Mango C.-T. Chao","orcid":"https://orcid.org/0000-0002-7299-9015"},"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":"Mango Chia-Tso Chao","raw_affiliation_strings":["Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Electronics, National Chiao Tung University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":11,"corresponding_author_ids":["https://openalex.org/A5024940546"],"corresponding_institution_ids":["https://openalex.org/I148366613"],"apc_list":null,"apc_paid":null,"fwci":1.1769,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78127311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10876","display_name":"Fault Detection and Control Systems","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9951000213623047,"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/T10320","display_name":"Neural Networks and Applications","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/iddq-testing","display_name":"Iddq testing","score":0.8294572830200195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6609216928482056},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6534064412117004},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6090534925460815},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4821205139160156},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.475582480430603},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46721401810646057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36875462532043457},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33533746004104614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3311079144477844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2947652041912079},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18350830674171448},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1364828646183014},{"id":"https://openalex.org/keywords/cmos","display_name":"CMOS","score":0.07709360122680664}],"concepts":[{"id":"https://openalex.org/C206678392","wikidata":"https://www.wikidata.org/wiki/Q5987815","display_name":"Iddq testing","level":3,"score":0.8294572830200195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6609216928482056},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6534064412117004},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6090534925460815},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4821205139160156},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.475582480430603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46721401810646057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36875462532043457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33533746004104614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3311079144477844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2947652041912079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18350830674171448},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1364828646183014},{"id":"https://openalex.org/C46362747","wikidata":"https://www.wikidata.org/wiki/Q173431","display_name":"CMOS","level":2,"score":0.07709360122680664},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vts48691.2020.9107570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts48691.2020.9107570","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 38th VLSI Test Symposium (VTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1527363716","https://openalex.org/W1579853615","https://openalex.org/W1967683336","https://openalex.org/W2011955149","https://openalex.org/W2028990781","https://openalex.org/W2091758325","https://openalex.org/W2099803635","https://openalex.org/W2099807755","https://openalex.org/W2116996377","https://openalex.org/W2120859640","https://openalex.org/W2121399123","https://openalex.org/W2130404536","https://openalex.org/W2131862714","https://openalex.org/W2142898772","https://openalex.org/W2147198689","https://openalex.org/W2158176397","https://openalex.org/W2168209902","https://openalex.org/W2168946591","https://openalex.org/W2570435998","https://openalex.org/W2585209422","https://openalex.org/W2893995718","https://openalex.org/W2963190151","https://openalex.org/W4241008425","https://openalex.org/W4247409213","https://openalex.org/W6634817459","https://openalex.org/W6733396966","https://openalex.org/W6755463424"],"related_works":["https://openalex.org/W2164017138","https://openalex.org/W2181536841","https://openalex.org/W2946329844","https://openalex.org/W2121399123","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"In":[0,62],"order":[1],"to":[2,49,91,153,186],"reduce":[3],"DPPM":[4],"(defect":[5],"parts":[6],"per":[7],"million),":[8],"IDDQ":[9,32,80,101,113],"testing":[10,33],"methodology":[11],"can":[12,87,158],"be":[13,88,159],"exploited":[14],"for":[15],"identifying":[16],"\"outliers\"":[17],"which":[18,191],"are":[19,45,58],"potentially":[20],"defective":[21],"but":[22],"not":[23],"detected":[24],"by":[25,65,127],"signoff":[26],"functional":[27],"and":[28,95,103,173,176],"parametric":[29],"tests.":[30],"Conventional":[31],"paradigms":[34],"depending":[35],"on":[36,136],"a":[37,67,82,129],"simple":[38],"statistical":[39],"6\u03c3":[40],"rule":[41],"or":[42],"engineers\u2019":[43],"experience":[44],"usually":[46],"too":[47],"conservative":[48],"effectively":[50],"identify":[51,104],"non-trivial":[52],"outliers,":[53],"especially":[54],"when":[55],"spatial":[56,150],"correlations":[57,151],"of":[59,78,81,140,147,170,179,195],"great":[60],"concern/influence.":[61],"this":[63],"paper,":[64],"employing":[66],"stochastic":[68,122],"regression":[69,123],"model,":[70],"the":[71,76,79,92,105,117,177,187,193],"mean":[72,94],"as":[73,75,107],"well":[74],"variance":[77],"die":[83],"under":[84],"test":[85],"(DUT)":[86],"predicted.":[89],"According":[90],"predicted":[93],"variance,":[96],"we":[97],"derive":[98],"an":[99,108],"expected":[100,118],"range":[102],"DUT":[106],"outlier":[109],"if":[110],"its":[111,137],"actual":[112],"measurement":[114],"is":[115,125,165,183],"beyond":[116],"range.":[119],"The":[120,161],"proposed":[121,197],"model":[124],"obtained":[126],"training":[128],"convolutional":[130,141],"neural":[131],"network":[132],"(CNN)":[133],"and,":[134],"based":[135],"primitive":[138],"property":[139],"kernel":[142],"mapping":[143],"with":[144],"large":[145],"volume":[146],"industrial":[148],"data,":[149],"(due":[152],"spatially-correlated":[154],"process":[155],"variations,":[156],"etc)":[157],"considered/captured.":[160],"trained":[162],"data-driven":[163],"CNN":[164],"highly":[166],"accurate":[167],"in":[168],"terms":[169],"R-square":[171],"(0.958)":[172],"RMSE":[174],"(0.783),":[175],"percentage":[178],"identified":[180],"outliers":[181],"(0.047%)":[182],"very":[184],"close":[185],"theoretical":[188],"reference":[189],"(0.050%),":[190],"validates":[192],"efficacy":[194],"our":[196],"methodology.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}