Search Results for author: Hao-Chiang Shao

Found 5 papers, 1 papers with code

Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning

no code implementations24 Jan 2022 Hao-Chiang Shao, Hsing-Lei Ping, Kuo-shiuan Chen, Weng-Tai Su, Chia-Wen Lin, Shao-Yun Fang, Pin-Yian Tsai, Yan-Hsiu Liu

To address the problem, we propose a deep learning-based layout novelty detection scheme to identify novel (unseen) layout patterns, which cannot be well predicted by a pre-trained pre-simulation model.

Active Learning Novelty Detection

Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction

no code implementations13 Mar 2021 Hao-Chiang Shao, Hsin-Chieh Wang, Weng-Tai Su, Chia-Wen Lin

Here we focus on the problem that noisy labels are primarily mislabeled samples, which tend to be concentrated near decision boundaries, rather than uniformly distributed, and whose features should be equivocal.

Ensemble Learning

DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition

no code implementations23 Feb 2020 Hao-Chiang Shao, Kang-Yu Liu, Chia-Wen Lin, Jiwen Lu

With their aid, DotFAN can learn a disentangled face representation and effectively generate face images of various facial attributes while preserving the identity of augmented faces.

Face Recognition

From IC Layout to Die Photo: A CNN-Based Data-Driven Approach

no code implementations11 Feb 2020 Hao-Chiang Shao, Chao-Yi Peng, Jun-Rei Wu, Chia-Wen Lin, Shao-Yun Fang, Pin-Yen Tsai, Yan-Hsiu Liu

By learning the shape correspondences between pairs of layout design patterns and their scanning electron microscope (SEM) images of the product wafer thereof, given an IC layout pattern, LithoNet can mimic the fabrication process to predict its fabricated circuit shape.

Layout Design

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