13 citations · 33 across the 5 of their papers we have counts for
5 papers
FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving
Tengju Ye, Wei Jing, Chunyong Hu +11
Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving. However, leveraging such…
A Deep Learning Technique using a Sequence of Follow Up X-Rays for Disease classification
Sairamvinay Vijayaraghavan, David Haddad, Shikun Huang +1
The ability to predict lung and heart based diseases using deep learning techniques is central to many researchers, particularly in the medical field around the world. In this pape…
Interpretable Compositional Convolutional Neural Networks
Wen Shen, Zhihua Wei, Shikun Huang +4
The reasonable definition of semantic interpretability presents the core challenge in explainable AI. This paper proposes a method to modify a traditional convolutional neural netw…
Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing
Wen Shen, Zhihua Wei, Shikun Huang +4
In this paper, we diagnose deep neural networks for 3D point cloud processing to explore utilities of different intermediate-layer network architectures. We propose a number of hyp…
3D-Rotation-Equivariant Quaternion Neural Networks
Wen Shen, Binbin Zhang, Shikun Huang +2
This paper proposes a set of rules to revise various neural networks for 3D point cloud processing to rotation-equivariant quaternion neural networks (REQNNs). We find that when a…