no code implementations • 24 Apr 2024 • Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee
Latency attacks against object detection represent a variant of adversarial attacks that aim to inflate the inference time by generating additional ghost objects in a target image.
no code implementations • 11 Apr 2023 • Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung, Che-Rung Lee
Nowadays, the deployment of deep learning-based applications is an essential task owing to the increasing demands on intelligent services.
no code implementations • 7 Dec 2021 • Bo-Shiuan Chu, Che-Rung Lee
Tensor decomposition is one of the fundamental technique for model compression of deep convolution neural networks owing to its ability to reveal the latent relations among complex structures.
1 code implementation • 3 Nov 2021 • Erh-Chung Chen, Che-Rung Lee
Despite the popularity of neural network models, a significant gap exists between the natural and robust accuracy of these models.
no code implementations • 3 Dec 2018 • Wei-Chun Chen, Chia-Che Chang, Chien-Yu Lu, Che-Rung Lee
One promising method is knowledge distillation (KD), which creates a fast-to-execute student model to mimic a large teacher network.
1 code implementation • ECCV 2018 • Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
Generative adversarial networks (GANs) often suffer from unpredictable mode-collapsing during training.
Ranked #26 on Image Generation on CelebA 64x64