Machine Learning-based Anomaly Detection for Post-silicon Bug Diagnosis

Author:

DeOrio Andrew,Li Qingkun,Burgess Matthew,Bertacco Valeria

Publisher

IEEE Conference Publications

Cited by 7 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. Experts in the Loop: Conditional Variable Selection Based on Deep Learning for Accelerating Post-Silicon Validation;IEEE Transactions on Semiconductor Manufacturing;2024-05

2. A Simple Confidence-Supervised Model for High-Resolution Defect Recognition;2024 8th International Conference on Robotics, Control and Automation (ICRCA);2024-01-12

3. A Comprehensive Review of Machine Learning Applications in VLSI Testing: Unveiling the Future of Semiconductor Manufacturing;2023 7th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech);2023-12-18

4. Interactive Analysis of Post-Silicon Validation Data;2022 First International Workshop on Visualization in Testing of Hardware, Software, and Manufacturing (TestVis);2022-10

5. Adaptive Feedback Mechanism for Silicon Bug Detection;Lecture Notes in Electrical Engineering;2021

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