Machine Learning in Integrated Circuit Substrate Electrical Test (IMPACT 2023)-Reference-Cited by-同舟云学术

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Machine Learning in Integrated Circuit Substrate Electrical Test (IMPACT 2023)

Published:2023-10-25 Issue: Volume: Page:
ISSN:
Container-title:2023 18th International Microsystems, Packaging, Assembly and Circuits Technology Conference (IMPACT)
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Author:

Lai Jung-Pin¹,Lin Ying-Lei²,Liu Yu-Hui²,Lin Ho-Chuan³,Shih Chih-Yuan³,Wang Yu-Po³,Pai Ping-Feng⁴

Affiliation:

1. HungKuang University,Department of Multimedia Game Development and Application,Taichung City 433,Taiwan (R.O.C.),433304

2. National Chi Nan University,PhD Program in Strategy and Development of Emerging Industries,Nantou County 545,Taiwan (R.O.C.),545301

3. Siliconware Precision Industries Co., Ltd.,Taichung City 427,Taiwan (R.O.C.),42749

4. National Chi Nan University,Department of Information Management,Nantou County 545,Taiwan (R.O.C.),545301

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10348606/10348630/10348736.pdf?arnumber=10348736

Reference28 articles.

1. Artificial Neural Networks Based Optimization Techniques: A Review

2. Machine learning for board-level drop response of BGA packaging structure

3. Hierarchical Attention-Based Machine Learning Model for Radiation Prediction of WB-BGA Package

4. Effective Computational Approach for Optimization of Temperature on Printed Circuit Board

5. Machine Learning assisted Structural Design Optimization for Flip Chip Packages

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