Towards Fast and Robust Adversarial Training for Image Classification. - Erh-Chung Chen; Che-Rung Lee (ACCV (3), 2020)

FOCM: Faster Octave Convolution Using Mix-scaling. - Kuan-Hsian Hsieh; Erh-Chung Chen; Che-Rung Lee (TAAI, 2021)

LTD: Low Temperature Distillation for Robust Adversarial Training. - Erh-Chung Chen; Che-Rung Lee (CoRR, 2021)

Latency Attack Resilience in Object Detectors: Insights from Computing Architecture. - Erh-Chung Chen; Pin-Yu Chen; I-Hsin Chung; Che-Rung Lee (ACCV (8), 2024)

Overload: Latency Attacks on Object Detection for Edge Devices. - Erh-Chung Chen; Pin-Yu Chen; I-Hsin Chung; Che-Rung Lee (CVPR, 2024)

Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks. - Erh-Chung Chen; Pin-Yu Chen; I-Hsin Chung; Che-Rung Lee (CoRR, 2024)

Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness. - Erh-Chung Chen; Pin-Yu Chen; I-Hsin Chung; Che-Rung Lee (CoRR, 2024)

Data filtering for efficient adversarial training. - Erh-Chung Chen; Che-Rung Lee (Pattern Recognit., 2024)