most citedMask-guided Vision Transformer (MG-ViT) for Few-Shot Learning

10 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20222 cited

BI AVAN: Brain inspired Adversarial Visual Attention Network

Heng Huang, Lin Zhao, Xintao Hu +4

Visual attention is a fundamental mechanism in the human brain, and it inspires the design of attention mechanisms in deep neural networks. However, most of the visual attention st…

q-bio.NC20221 cited

Representing Brain Anatomical Regularity and Variability by Few-Shot Embedding

Lu Zhang, Xiaowei Yu, Yanjun Lyu +7

Effective representation of brain anatomical architecture is fundamental in understanding brain regularity and variability. Despite numerous efforts, it is still difficult to infer…

cs.CV20221 cited

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…

cs.CV202210 cited

Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning

Yuzhong Chen, Zhenxiang Xiao, Lin Zhao +10

Learning with little data is challenging but often inevitable in various application scenarios where the labeled data is limited and costly. Recently, few-shot learning (FSL) gaine…

q-bio.NC2021

Representative Functional Connectivity Learning for Multiple Clinical groups in Alzheimer's Disease

Lu Zhang, Xiaowei Yu, Yanjun Lyu +2

Mild cognitive impairment (MCI) is a high-risk dementia condition which progresses to probable Alzheimer's disease (AD) at approximately 10% to 15% per year. Characterization of gr…