Test And Reliability Improvement With Defect-Image Classification And Machine-Learning Algorithms In Semiconductor Industry For Automotive Applications-Reference-Cited by-同舟云学术

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Test And Reliability Improvement With Defect-Image Classification And Machine-Learning Algorithms In Semiconductor Industry For Automotive Applications

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA)
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Author:

Bergès Corinne¹,Zhang Shilu²,Létévé Audrey³,Anilturk Onder²,Bird Jim⁴,Lumanauw Edwin²,Shroff Mehul D.²,Hakem Zulkifli Azizul⁵,Foo Loke Sheng⁵,Choo Shengzi⁵,Smith Chris²

Affiliation:

1. NXP,France

2. NXP,Austin,United States

3. H2O Driverless AI,Edinburgh,UK

4. NXP,Chandler,United States

5. NXP,Kuala Lumpur,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10248978/10248979/10249118.pdf?arnumber=10249118

Reference11 articles.

1. SP1 Brightfield Defect Detection;cheh;KLA-Tencor application note,2003

2. Detection of a New Surface Killer Defect on Starting Si Material using Nomarski Principle of Differential Interference Contrast

3. Data analytics and machine learning: root-cause problem-solving approach to prevent yield loss and quality issues in semiconductor industry for automotive applications

4. Detection and prevention of assembly defects, by machine learning algorithms, in semiconductor industry for automotive

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