4 citations · 7 across the 5 of their papers we have counts for
5 papers
A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
Yunzhi Tian, Dekui Wang, Qirong Bu +3
Multi-view learning has been widely applied for sleep stage classification using multi-modal data. However, existing methods typically assume that different modalities are well-ali…
VTPNet for 3D deep learning on point cloud
Wei Zhou, Weiwei Jin, Qian Wang +4
Recently, Transformer-based methods for point cloud learning have achieved good results on various point cloud learning benchmarks. However, since the attention mechanism needs to…
GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentation
Wei Zhou, Qian Wang, Weiwei Jin +2
Recently, graph-based and Transformer-based deep learning networks have demonstrated excellent performances on various point cloud tasks. Most of the existing graph methods are bas…
Multi Point-Voxel Convolution (MPVConv) for Deep Learning on Point Clouds
Wei Zhou, Xin Cao, Xiaodan Zhang +3
The existing 3D deep learning methods adopt either individual point-based features or local-neighboring voxel-based features, and demonstrate great potential for processing 3D data…
Multi Voxel-Point Neurons Convolution (MVPConv) for Fast and Accurate 3D Deep Learning
Wei Zhou, Xin Cao, Xiaodan Zhang +3
We present a new convolutional neural network, called Multi Voxel-Point Neurons Convolution (MVPConv), for fast and accurate 3D deep learning. The previous works adopt either indiv…