Improving Test Quality of Memory Chips by a Decision Tree-Based Screening Method
Author:
Affiliation:
1. National Cheng Kung University,Department of Electrical Engineering,Tainan,Taiwan
2. National Tsing Hua University,Department of Electrical Engineering,Hsinchu,Taiwan
3. Taiwan Semiconductor Manufacturing Co., Ltd.,Hsinchu,Taiwan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9983856/9983857/09983925.pdf?arnumber=9983925
Reference14 articles.
1. Improving the Quality of Semiconductor Products with Enhanced Decision Tree and Random Forest;fang;Proc VLSI Test Technology Workshop (VTTW),2021
2. Machine Learning Interpretability: A Survey on Methods and Metrics
3. JEDEC Standard 22-A108-Temperature, Bias, and Operating Life;Rev-F JEDEC,2017
4. A Machine Learning-based Approach for Failure Prediction at Cell Level based on Wafer Acceptance Test Parameters
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