{"id":"https://openalex.org/W3002607153","doi":"https://doi.org/10.1109/newcas44328.2019.8961246","title":"Using deep learning approaches to overcome limited dataset issues within semiconductor domain","display_name":"Using deep learning approaches to overcome limited dataset issues within semiconductor domain","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W3002607153","doi":"https://doi.org/10.1109/newcas44328.2019.8961246","mag":"3002607153"},"language":"en","primary_location":{"id":"doi:10.1109/newcas44328.2019.8961246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/newcas44328.2019.8961246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 17th IEEE International New Circuits and Systems Conference (NEWCAS)","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/A5017100856","display_name":"Milad Omrani Tamrin","orcid":null},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Milad Omrani Tamrin","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034215962","display_name":"S\u00e9bastien Henwood","orcid":"https://orcid.org/0000-0002-4198-8487"},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sebastien Henwood","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037634323","display_name":"Jean-Francois Dubois","orcid":null},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jean-Fran\u00e7ois Dubois","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090465684","display_name":"Jean\u2010Jules Brault","orcid":null},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jean-Jules Brault","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061672323","display_name":"Saad Chidami","orcid":null},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Saad Chidami","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111849245","display_name":"Samuel-Jean Bassetto","orcid":null},"institutions":[{"id":"https://openalex.org/I45683168","display_name":"Polytechnique Montr\u00e9al","ror":"https://ror.org/05f8d4e86","country_code":"CA","type":"education","lineage":["https://openalex.org/I45683168"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Samuel-Jean Bassetto","raw_affiliation_strings":["Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","Polytechnique Montreal, Montr\u00e9al, QC, CANADA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnique Montreal,Montr&#x00E9;al,QC,CANADA","institution_ids":["https://openalex.org/I45683168"]},{"raw_affiliation_string":"Polytechnique Montreal, Montr\u00e9al, QC, CANADA","institution_ids":["https://openalex.org/I45683168"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45683168"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","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/T10472","display_name":"Semiconductor materials and devices","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.6979610919952393},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5587676763534546},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5445788502693176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4840890169143677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37517648935317993},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3420830965042114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05552232265472412}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6979610919952393},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5587676763534546},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5445788502693176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4840890169143677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37517648935317993},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3420830965042114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05552232265472412},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/newcas44328.2019.8961246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/newcas44328.2019.8961246","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 17th IEEE International New Circuits and Systems Conference (NEWCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:publications.polymtl.ca:44375","is_oa":false,"landing_page_url":"https://publications.polymtl.ca/44375/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401013","display_name":"PolyPublie (\u00c9cole Polytechnique de Montr\u00e9al)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45683168","host_organization_name":"Polytechnique Montr\u00e9al","host_organization_lineage":["https://openalex.org/I45683168"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Communication de conf\u00e9rence"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1959608418","https://openalex.org/W2013927912","https://openalex.org/W2099471712","https://openalex.org/W2117130368","https://openalex.org/W2170858534","https://openalex.org/W2337735138","https://openalex.org/W2489751196","https://openalex.org/W2884581909","https://openalex.org/W2899771611","https://openalex.org/W2950378732","https://openalex.org/W2963226019","https://openalex.org/W2963799213","https://openalex.org/W2963803174","https://openalex.org/W2964121744","https://openalex.org/W2970014727","https://openalex.org/W4320013936","https://openalex.org/W6684630340","https://openalex.org/W6718140377","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Today,":[0],"in":[1,81,101,183],"semiconductor":[2,61],"manufacturing,":[3],"wafer":[4,78],"failures":[5,55],"are":[6,19,33,80],"frequent":[7],"problems":[8],"with":[9],"the":[10,15,20,50,70,77,87,110,131,157,175,189],"production":[11,16,43],"lines.":[12],"To":[13],"increase":[14],"yield,":[17],"images":[18,59],"most":[21,82],"important":[22],"pieces":[23],"of":[24,53,133,149,156],"data":[25,142],"used":[26],"to":[27,41,68,89,118,123,153,167,193],"detect":[28,49,97],"defect-free":[29],"wafers.":[30],"However,":[31,127],"there":[32],"many":[34],"tools":[35],"that":[36,93,174],"can":[37],"be":[38,119],"installed":[39],"specifically":[40],"monitor":[42],"lines,":[44],"inspect":[45],"mapped":[46],"defects":[47],"and":[48,96,165],"main":[51],"causes":[52],"die":[54],"by":[56],"using":[57],"wafers":[58],"during":[60],"manufacturing":[62],"process.":[63],"The":[64,147],"underlying":[65],"objective":[66],"is":[67,105,138,145,152],"overcome":[69,124,168],"need":[71,88],"for":[72,109],"a":[73,91,106,120,179,184],"physical":[74],"check":[75],"on":[76,130,143],"which":[79,137],"cases":[83],"too":[84],"long.":[85],"Thus,":[86],"have":[90,116],"design":[92],"will":[94],"measure":[95],"these":[98],"visual":[99],"faults":[100],"an":[102],"automated":[103],"fashion":[104],"big":[107],"challenge":[108],"industry.":[111],"Recently,":[112],"deep":[113,159],"learning":[114,160],"approaches":[115],"proven":[117],"suitable":[121],"way":[122],"this":[125,150,169],"issue.":[126],"they":[128],"rely":[129],"availability":[132],"sufficiently":[134],"representative":[135],"datasets":[136],"not":[139],"our":[140],"case:":[141],"anomalies":[144],"scarce.":[146],"goal":[148],"paper":[151],"evaluate":[154],"state":[155],"art":[158],"methodology":[161],"such":[162],"as":[163],"GAN":[164,176],"VAE":[166,190],"challenge.":[170],"Implementation":[171],"results":[172],"show":[173],"architecture":[177,191],"achieves":[178],"convincing":[180],"image":[181],"generation":[182],"limited":[185],"sample":[186],"setting,":[187],"while":[188],"fails":[192],"converge":[194],"at":[195],"training":[196],"time.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
