9 citations · 16 across the 4 of their papers we have counts for
9 papers
RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes
Po-Wei Wu, Yu-Jing Lin, Che-Han Chang +2
Multi-domain image-to-image translation has gained increasing attention recently. Previous methods take an image and some target attributes as inputs and generate an output image w…
Effective Medical Test Suggestions Using Deep Reinforcement Learning
Yang-En Chen, Kai-Fu Tang, Yu-Shao Peng +1
Effective medical test suggestions benefit both patients and physicians to conserve time and improve diagnosis accuracy. In this work, we show that an agent can learn to suggest ef…
G2R Bound: A Generalization Bound for Supervised Learning from GAN-Synthetic Data
Fu-Chieh Chang, Hao-Jen Wang, Chun-Nan Chou +1
Performing supervised learning from the data synthesized by using Generative Adversarial Networks (GANs), dubbed GAN-synthetic data, has two important applications. First, GANs may…
KG-GAN: Knowledge-Guided Generative Adversarial Networks
Che-Han Chang, Chun-Hsien Yu, Szu-Ying Chen +1
Can generative adversarial networks (GANs) generate roses of various colors given only roses of red petals as input? The answer is negative, since GANs' discriminator would reject…
MBS: Macroblock Scaling for CNN Model Reduction
Yu-Hsun Lin, Chun-Nan Chou, Edward Y. Chang
In this paper we propose the macroblock scaling (MBS) algorithm, which can be applied to various CNN architectures to reduce their model size. MBS adaptively reduces each CNN macro…
BRIEF: Backward Reduction of CNNs with Information Flow Analysis
Yu-Hsun Lin, Chun-Nan Chou, Edward Y. Chang
This paper proposes BRIEF, a backward reduction algorithm that explores compact CNN-model designs from the information flow perspective. This algorithm can remove substantial non-z…