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SEM image denoising with Unsupervised Machine Learning for better defect inspection and metrology

dc.contributor.authorDey, Bappaditya
dc.contributor.authorHalder, Sandip
dc.contributor.authorKhalil, K.
dc.contributor.authorLorusso, Gian
dc.contributor.authorSeveri, Joren
dc.contributor.authorLeray, Philippe
dc.contributor.authorBayoumi, M.
dc.date.accessioned2021-10-31T08:28:53Z
dc.date.available2021-10-31T08:28:53Z
dc.date.issued2021
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/36666
dc.sourceIIOimport
dc.titleSEM image denoising with Unsupervised Machine Learning for better defect inspection and metrology
dc.typeProceedings paper
dc.contributor.imecauthorDey, Bappaditya
dc.contributor.imecauthorHalder, Sandip
dc.contributor.imecauthorLorusso, Gian
dc.contributor.imecauthorSeveri, Joren
dc.contributor.imecauthorLeray, Philippe
dc.contributor.orcidimecDey, Bappaditya::0000-0002-0886-137X
dc.contributor.orcidimecHalder, Sandip::0000-0002-6314-2685
dc.source.peerreviewyes
dc.source.beginpage1161115
dc.source.conferenceMetrology, Inspection, and Process Control for Semiconductor Manufacturing XXXV
dc.source.conferencedate21/02/2021
dc.source.conferencelocationDigital Forum USA
dc.identifier.urlhttps://doi.org/10.1117/12.2584803
imec.availabilityPublished - imec
imec.internalnotesProceedings of SPIE; Vol. 11611


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