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

author
Selg, Hardi
Jenihhin, Maksim
Ellervee, Peeter
statement of authorship
Hardi Selg, Maksim Jenihhin, Peeter Ellervee
source
21st IEEE Latin-American Test Symposium (LATS) 2020 : proceedings
location of publication
Danvers
publisher
IEEE
year of publication
2020
pages
5 p
conference location
Maceio, Brazil
url
https://doi.org/10.1109/LATS49555.2020.9093672
subject term
tehisõpe
testimine
keyword
machine learning (ML)
Die Inking
wafer testing
ISSN
2373-0862
notes
Bibliogr.: 19 ref
TTÜ department
arvutisüsteemide instituut
language
inglise
Uurimisrühm
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