41 citations · 42 across the 4 of their papers we have counts for
4 papers
Exploring "Many in Few" and "Few in Many" Properties in Long-Tailed, Highly-Imbalanced IC Defect Classification
Hao-Chiang Shao, Chun-Hao Chang, Yu-Hsien Lin +3
Despite significant advancements in deep classification techniques and in-lab automatic optical inspection models for long-tailed or highly imbalanced data, applying these approach…
LithoHoD: A Litho Simulator-Powered Framework for IC Layout Hotspot Detection
Hao-Chiang Shao, Guan-Yu Chen, Yu-Hsien Lin +4
Recent advances in VLSI fabrication technology have led to die shrinkage and increased layout density, creating an urgent demand for advanced hotspot detection techniques. However,…
Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning
Hao-Chiang Shao, Hsing-Lei Ping, Kuo-shiuan Chen +5
Learning-based pre-simulation (i.e., layout-to-fabrication) models have been proposed to predict the fabrication-induced shape deformation from an IC layout to its fabricated circu…
From IC Layout to Die Photo: A CNN-Based Data-Driven Approach
Hao-Chiang Shao, Chao-Yi Peng, Jun-Rei Wu +4
We propose a deep learning-based data-driven framework consisting of two convolutional neural networks: i) LithoNet that predicts the shape deformations on a circuit due to IC fabr…