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Automatic prediction of MOSFETs threshold voltage by machine learning algorithms

dc.contributor.authorChoi, Seoyeon
dc.contributor.authorPark, Dong Geun
dc.contributor.authorKim, Min Jung
dc.contributor.authorBang, Seain
dc.contributor.authorKim, Jungchun
dc.contributor.authorJin, Seunghee
dc.contributor.authorHuh, Ki Seok
dc.contributor.authorKim, Donghyun
dc.contributor.authorKim, Sanghyeok
dc.contributor.authorYoon, Inkyu
dc.contributor.authorMitard, Jerome
dc.contributor.authorHan, Cheol E.
dc.contributor.authorLee, Jae Woo
dc.date.accessioned2023-11-29T08:53:42Z
dc.date.available2023-09-03T17:38:59Z
dc.date.available2023-11-29T08:53:42Z
dc.date.issued2023
dc.identifier.issnna
dc.identifier.otherWOS:001004185500127
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/42460.2
dc.sourceWOS
dc.titleAutomatic prediction of MOSFETs threshold voltage by machine learning algorithms
dc.typeProceedings paper
dc.contributor.imecauthorMitard, Jerome
dc.contributor.orcidimecMitard, Jerome::0000-0002-7422-079X
dc.identifier.doi10.1109/EDTM55494.2023.10103059
dc.identifier.eisbn979-8-3503-3252-0
dc.source.numberofpages3
dc.source.peerreviewyes
dc.source.conference7th IEEE Electron Devices Technology and Manufacturing Conference (EDTM)
dc.source.conferencedateMAR 07-10, 2023
dc.source.conferencelocationSeoul
dc.source.journalna
imec.availabilityPublished - imec
dc.description.wosFundingTextThis research was supported by the National Research Foundation (NRF-2022R1A2C1010447, 2021R1F1A1063342), European Nanoelectronics Access (ASCENT+).


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220.500.12860/42460.2*2023-11-29T08:51:02Zvalidation by library/open access desk
120.500.12860/424602023-09-03T17:38:59Z

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