1.4k citations · 2k across the 12 of their papers we have counts for
8 papers · 1 filter
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security
Hao Dong, Chao Wu, Zhen Wei +1
Deep learning methods can play a crucial role in anomaly detection, prediction, and supporting decision making for applications like personal health-care, pervasive body sensing, e…
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Hao Dong, Akara Supratak, Luo Mai +4
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduo…
Semantic Image Synthesis via Adversarial Learning
Hao Dong, Simiao Yu, Chao Wu +1
In this paper, we propose a way of synthesizing realistic images directly with natural language description, which has many useful applications, e.g. intelligent image manipulation…
Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks
Hao Dong, Guang Yang, Fangde Liu +2
A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has…
Deep De-Aliasing for Fast Compressive Sensing MRI
Simiao Yu, Hao Dong, Guang Yang +8
Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clinical applications in order to reduce the scanning cost and improve the patient experience. This can also pote…
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation
Hao Dong, Jingqing Zhang, Douglas McIlwraith +1
Translating information between text and image is a fundamental problem in artificial intelligence that connects natural language processing and computer vision. In the past few ye…