activity
20172023
most citedSVSGAN: Singing Voice Separation via Generative Adversarial Network

5 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Learning Image Deraining Transformer Network with Dynamic Dual Self-Attention

Zhentao Fan, Hongming Chen, Yufeng Li

Recently, Transformer-based architecture has been introduced into single image deraining task due to its advantage in modeling non-local information. However, existing approaches t…

cs.SD2020★ 3 cited

Addressing the confounds of accompaniments in singer identification

Tsung-Han Hsieh, Kai-Hsiang Cheng, Zhe-Cheng Fan +2

Identifying singers is an important task with many applications. However, the task remains challenging due to many issues. One major issue is related to the confounding factors fro…

cs.LG2018

Backpropagation with N-D Vector-Valued Neurons Using Arbitrary Bilinear Products

Zhe-Cheng Fan, Tak-Shing T. Chan, Yi-Hsuan Yang +1

Vector-valued neural learning has emerged as a promising direction in deep learning recently. Traditionally, training data for neural networks (NNs) are formulated as a vector of s…

cs.SD2017★ 5 cited

SVSGAN: Singing Voice Separation via Generative Adversarial Network

Zhe-Cheng Fan, Yen-Lin Lai, Jyh-Shing Roger Jang

Separating two sources from an audio mixture is an important task with many applications. It is a challenging problem since only one signal channel is available for analysis. In th…

cs.SD2017

Music Signal Processing Using Vector Product Neural Networks

Z. C. Fan, T. S. Chan, Y. H. Yang +1

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real val…