17 citations · 86 across the 28 of their papers we have counts for
6 papers · 1 filter
A Self-Learning Multimodal Approach for Fake News Detection
Hao Chen, Hui Guo, Baochen Hu +5
The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While mach…
Meta-Learning with Heterogeneous Tasks
Zhaofeng Si, Shu Hu, Kaiyi Ji +1
Meta-learning is a general approach to equip machine learning models with the ability to handle few-shot scenarios when dealing with many tasks. Most existing meta-learning methods…
An Explainable Non-local Network for COVID-19 Diagnosis
Jingfu Yang, Peng Huang, Jing Hu +5
The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to…
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection
Peng Huang, Shu Hu, Bo Peng +3
Current medical image classification efforts mainly aim for higher average performance, often neglecting the balance between different classes. This can lead to significant differe…
Masked Conditional Diffusion Model for Enhancing Deepfake Detection
Tiewen Chen, Shanmin Yang, Shu Hu +4
Recent studies on deepfake detection have achieved promising results when training and testing faces are from the same dataset. However, their results severely degrade when confron…
Efficient Image Super-Resolution via Symmetric Visual Attention Network
Chengxu Wu, Qinrui Fan, Shu Hu +3
An important development direction in the Single-Image Super-Resolution (SISR) algorithms is to improve the efficiency of the algorithms. Recently, efficient Super-Resolution (SR)…