Performing Machine Learning Based Outlier Detection for Automotive Grade Products-Reference-Cited by-同舟云学术

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Performing Machine Learning Based Outlier Detection for Automotive Grade Products

Published:2023-03 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Reliability Physics Symposium (IRPS)
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Author:

Yang Y.L.¹,Tsao P.C.¹,Lin C.W.¹,Lee Ross¹,Ni Olivia¹,Chen T.T.¹,Ting Y.J.¹,Lai C.T.¹,Yeh Jason¹,Yang Arnold¹,Huang Wayne¹,Chen Peng¹,Tsai Charly¹,Yang Ryan¹,Huang Y.S.¹,Hsu B.C.¹,Lee M.Z.¹,Lee T.H.¹,Huang Michael¹,Chen Coming¹,Chu Liham¹,Kao H.W.¹,Tsai N.S.¹

Affiliation:

1. MediaTek Inc.,Hsinchu,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10117589/10117581/10118207.pdf?arnumber=10118207

Reference14 articles.

1. Guidelines for statistical yield analysis;Automotive Electronic Council,2000

2. Guidelines for part average testing;Automotive Electronic Council,2011

3. Advanced Outlier Detection Using Unsupervised Learning for Screening Potential Customer Returns

4. Applying Universal Chip Telemetry to Detect Latent Defects and Aging in Advanced Electronics

5. A novel approach to in-field, in-mission reliability monitoring based on Deep Data

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Vmin Shift Prediction Using Machine Learning-Based Methodology for Automotive Products;2024 IEEE International Reliability Physics Symposium (IRPS);2024-04-14

2. Utilizing Transformer Deep Learning Based Outlier Detection to Screen Out Reliability Weak ICs;2024 IEEE International Reliability Physics Symposium (IRPS);2024-04-14

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