83 citations · 116 across the 5 of their papers we have counts for
7 papers
Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer
Yuzhen Ding, Hongying Feng, Yunze Yang +9
Purpose: In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed imaging is available. The v…
Discovering Dynamic Functional Brain Networks via Spatial and Channel-wise Attention
Yiheng Liu, Enjie Ge, Mengshen He +6
Using deep learning models to recognize functional brain networks (FBNs) in functional magnetic resonance imaging (fMRI) has been attracting increasing interest recently. However,…
Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning
Chong Ma, Lin Zhao, Yuzhong Chen +15
Learning harmful shortcuts such as spurious correlations and biases prevents deep neural networks from learning the meaningful and useful representations, thus jeopardizing the gen…
Can Attention Enable MLPs To Catch Up With CNNs?
Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu +3
In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17]…
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu +1
Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks. Self-attention updates the feature at e…
PCT: Point cloud transformer
Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu +3
The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing. This paper presents a novel framework named Point Cloud Tra…