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Wafer-level die re-test success prediction using machine learning

author
statement of authorship
Hardi Selg, Maksim Jenihhin, Peeter Ellervee
source
21st IEEE Latin-American Test Symposium (LATS) 2020 : proceedings
location of publication
Danvers
publisher
year of publication
pages
5 p
conference location
Maceio, Brazil
url
ISSN
2373-0862
notes
Bibliogr.: 19 ref
TTÜ department
language
inglise
subject term
keyword
machine learning (ML)
Die Inking
wafer testing
Reserch Group
Centre for trustworthy and efficient computing hardware (TECH)
Selg, H., Jenihhin, M., Ellervee, P. Wafer-level die re-test success prediction using machine learning // 21st IEEE Latin-American Test Symposium (LATS) 2020 : proceedings. Danvers : IEEE, 2020. 5 p. https://doi.org/10.1109/LATS49555.2020.9093672