2 citations · 3 across the 3 of their papers we have counts for
6 papers
Adversarial Data Encryption
Yingdong Hu, Liang Zhang, Wei Shan +4
In the big data era, many organizations face the dilemma of data sharing. Regular data sharing is often necessary for human-centered discussion and communication, especially in med…
AIRNet: Self-Supervised Affine Registration for 3D Medical Images using Neural Networks
Evelyn Chee, Zhenzhou Wu
In this work, we propose a self-supervised learning method for affine image registration on 3D medical images. Unlike optimisation-based methods, our affine image registration netw…
Character-Based Text Classification using Top Down Semantic Model for Sentence Representation
Zhenzhou Wu, Xin Zheng, Daniel Dahlmeier
Despite the success of deep learning on many fronts especially image and speech, its application in text classification often is still not as good as a simple linear SVM on n-gram…
HiNet: Hierarchical Classification with Neural Network
Zhenzhou Wu, Sean Saito
Traditionally, classifying large hierarchical labels with more than 10000 distinct traces can only be achieved with flatten labels. Although flatten labels is feasible, it misses t…
Multi-Modal Hybrid Deep Neural Network for Speech Enhancement
Zhenzhou Wu, Sunil Sivadas, Yong Kiam Tan +2
Deep Neural Networks (DNN) have been successful in en- hancing noisy speech signals. Enhancement is achieved by learning a nonlinear mapping function from the features of the corru…
Deep Denoising Auto-encoder for Statistical Speech Synthesis
Zhenzhou Wu, Shinji Takaki, Junichi Yamagishi
This paper proposes a deep denoising auto-encoder technique to extract better acoustic features for speech synthesis. The technique allows us to automatically extract low-dimension…