{"id":"https://openalex.org/W2960345431","doi":"https://doi.org/10.1109/vts.2019.8758634","title":"IP Session on Machine Learning Applications in IC Test-Related Tasks","display_name":"IP Session on Machine Learning Applications in IC Test-Related Tasks","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2960345431","doi":"https://doi.org/10.1109/vts.2019.8758634","mag":"2960345431"},"language":"en","primary_location":{"id":"doi:10.1109/vts.2019.8758634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2019.8758634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 37th 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/A5021535037","display_name":"Ghada Sokar","orcid":null},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Ghada Sokar","raw_affiliation_strings":["Cairo University, Egypt"],"affiliations":[{"raw_affiliation_string":"Cairo University, Egypt","institution_ids":["https://openalex.org/I145487455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032766289","display_name":"Yassin Zakaria","orcid":"https://orcid.org/0000-0003-1770-7312"},"institutions":[{"id":"https://openalex.org/I145487455","display_name":"Cairo University","ror":"https://ror.org/03q21mh05","country_code":"EG","type":"education","lineage":["https://openalex.org/I145487455"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Yassien Zakaria","raw_affiliation_strings":["Cairo University, Egypt"],"affiliations":[{"raw_affiliation_string":"Cairo University, Egypt","institution_ids":["https://openalex.org/I145487455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055664696","display_name":"Asmaa H. Rabie","orcid":"https://orcid.org/0000-0003-3711-9788"},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Asmaa Rabie","raw_affiliation_strings":["A Siemens Business, USA"],"affiliations":[{"raw_affiliation_string":"A Siemens Business, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061563066","display_name":"Kareem Madkour","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kareem Madkour","raw_affiliation_strings":["A Siemens Business, USA"],"affiliations":[{"raw_affiliation_string":"A Siemens Business, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013576641","display_name":"Ira Leventhal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ira Leventhal","raw_affiliation_strings":["Advantest, USA"],"affiliations":[{"raw_affiliation_string":"Advantest, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037656346","display_name":"Jochen Rivoir","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jochen Rivoir","raw_affiliation_strings":["Advantest, Germany"],"affiliations":[{"raw_affiliation_string":"Advantest, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014106133","display_name":"Xinli Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146936","display_name":"Huawei Technologies (United States)","ror":"https://ror.org/03jyqk712","country_code":"US","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210146936"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinli Gu","raw_affiliation_strings":["Futurewei Technologies, Inc., Huawei, USA"],"affiliations":[{"raw_affiliation_string":"Futurewei Technologies, Inc., Huawei, USA","institution_ids":["https://openalex.org/I4210146936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091734149","display_name":"Haralampos\u2010G. Stratigopoulos","orcid":"https://orcid.org/0000-0002-9943-5607"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I51101395","display_name":"Universit\u00e9 Paris 1 Panth\u00e9on-Sorbonne","ror":"https://ror.org/002t25c44","country_code":"FR","type":"education","lineage":["https://openalex.org/I51101395"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Haralampos-G. Stratigopoulos","raw_affiliation_strings":["CNRS, Sorbonne Universit\u00e9, France (Organizer)"],"affiliations":[{"raw_affiliation_string":"CNRS, Sorbonne Universit\u00e9, France (Organizer)","institution_ids":["https://openalex.org/I39804081","https://openalex.org/I51101395","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5021535037"],"corresponding_institution_ids":["https://openalex.org/I145487455"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05821762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9983999729156494,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7045447826385498},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.6122860908508301},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5730851888656616},{"id":"https://openalex.org/keywords/curiosity","display_name":"Curiosity","score":0.5293553471565247},{"id":"https://openalex.org/keywords/learning-cycle","display_name":"Learning cycle","score":0.5021820068359375},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43127867579460144},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.42468202114105225},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.42150717973709106},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40948712825775146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38992875814437866},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11640411615371704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7045447826385498},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.6122860908508301},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5730851888656616},{"id":"https://openalex.org/C33435437","wikidata":"https://www.wikidata.org/wiki/Q366791","display_name":"Curiosity","level":2,"score":0.5293553471565247},{"id":"https://openalex.org/C2777432860","wikidata":"https://www.wikidata.org/wiki/Q6510168","display_name":"Learning cycle","level":2,"score":0.5021820068359375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43127867579460144},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.42468202114105225},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.42150717973709106},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40948712825775146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38992875814437866},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11640411615371704},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/vts.2019.8758634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vts.2019.8758634","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 37th VLSI Test Symposium (VTS)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.tue.nl:openaire_cris_publications/d80e8461-e420-4852-a77c-00b22b78c079","is_oa":false,"landing_page_url":"https://research.tue.nl/en/publications/d80e8461-e420-4852-a77c-00b22b78c079","pdf_url":null,"source":{"id":"https://openalex.org/S4406922641","display_name":"TU/e Research Portal","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sokar, G, Zakaria, Y, Rabie, A, Madkour, K, Leventhal, I, Rivoir, J, Gu, X & Stratigopoulos, H G 2019, IP Session on Machine Learning Applications in IC Test-Related Tasks. in 2019 IEEE 37th VLSI Test Symposium, VTS 2019., 8758634, IEEE Computer Society, 37th IEEE VLSI Test Symposium, VTS 2019, Monterey, United States, 23/04/19. https://doi.org/10.1109/VTS.2019.8758634","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:tue:oai:pure.tue.nl:publications/d80e8461-e420-4852-a77c-00b22b78c079","is_oa":false,"landing_page_url":"https://research.tue.nl/nl/publications/d80e8461-e420-4852-a77c-00b22b78c079","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 IEEE 37th VLSI Test Symposium, VTS 2019","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3094054656","https://openalex.org/W4285676344","https://openalex.org/W2123270665","https://openalex.org/W4382584175","https://openalex.org/W2060310955","https://openalex.org/W2284924956","https://openalex.org/W3043413210","https://openalex.org/W2613740288","https://openalex.org/W4252460700","https://openalex.org/W4383268304"],"abstract_inverted_index":{"Over":[0],"the":[1,41,80,88,96,106,107],"last":[2],"decade":[3],"there":[4],"has":[5],"been":[6,57],"a":[7,30,37],"surge":[8],"of":[9,32,40,82,90],"activity":[10],"in":[11,95],"employing":[12],"advanced":[13],"statistical":[14],"analysis":[15],"and":[16,68,71,100,102],"machine":[17,64,92],"learning":[18,65,84],"methods":[19],"to":[20,46,59],"various":[21,48],"test-related":[22],"tasks.":[23],"The":[24,75],"topic":[25],"is":[26],"no":[27],"longer":[28],"simply":[29],"matter":[31],"academic":[33],"curiosity":[34],"but,":[35],"rather,":[36],"pressing":[38],"need":[39],"industry":[42,54,98],"as":[43],"it":[44],"seeks":[45],"address":[47],"challenges.":[49],"In":[50],"this":[51],"session,":[52],"three":[53,76],"experts":[55],"have":[56],"invited":[58],"give":[60],"their":[61],"perspective,":[62],"describe":[63],"use":[66,81],"cases,":[67],"discuss":[69],"challenges":[70],"future":[72],"work":[73],"ideas.":[74],"talks":[77],"will":[78],"cover":[79],"deep":[83],"for":[85],"hotspot":[86],"detection,":[87],"challenge":[89],"rendering":[91],"learning-based":[93],"decisions":[94],"semiconductor":[97],"trustable":[99],"explainable,":[101],"data":[103],"analytics":[104],"across":[105],"complete":[108],"product":[109,113],"cycle":[110],"towards":[111],"improved":[112],"reliability.":[114]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}