61 citations · 177 across the 7 of their papers we have counts for
7 papers · 1 filter
Contrastive Multimodal Fusion with TupleInfoNCE
Yunze Liu, Qingnan Fan, Shanghang Zhang +3
This paper proposes a method for representation learning of multimodal data using contrastive losses. A traditional approach is to contrast different modalities to learn the inform…
Generative Creativity: Adversarial Learning for Bionic Design
Simiao Yu, Hao Dong, Pan Wang +2
Bionic design refers to an approach of generative creativity in which a target object (e.g. a floor lamp) is designed to contain features of biological source objects (e.g. flowers…
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…
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…