11 citations · 22 across the 6 of their papers we have counts for
6 papers
Overload: Latency Attacks on Object Detection for Edge Devices
Erh-Chung Chen, Pin-Yu Chen, I-Hsin Chung +1
Nowadays, the deployment of deep learning-based applications is an essential task owing to the increasing demands on intelligent services. In this paper, we investigate latency att…
Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization
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…
LTD: Low Temperature Distillation for Gradient Masking-free Adversarial Training
Erh-Chung Chen, Che-Rung Lee
Adversarial training is a widely adopted strategy to bolster the robustness of neural network models against adversarial attacks. This paper revisits the fundamental assumptions un…
Knowledge Distillation with Feature Maps for Image Classification
Wei-Chun Chen, Chia-Che Chang, Chien-Yu Lu +1
The model reduction problem that eases the computation costs and latency of complex deep learning architectures has received an increasing number of investigations owing to its imp…
Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer
Chien-Yu Lu, Min-Xin Xue, Chia-Che Chang +2
Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from t…
Escaping from Collapsing Modes in a Constrained Space
Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee +3
Generative adversarial networks (GANs) often suffer from unpredictable mode-collapsing during training. We study the issue of mode collapse of Boundary Equilibrium Generative Adver…