42 citations · 45 across the 4 of their papers we have counts for
5 papers · 1 filter
3D-model ShapeNet Core Classification using Meta-Semantic Learning
Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh +3
Understanding 3D point cloud models for learning purposes has become an imperative challenge for real-world identification such as autonomous driving systems. A wide variety of sol…
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical Images
Hongzheng Yang, Cheng Chen, Meirui Jiang +4
Test-time adaptation (TTA) has increasingly been an important topic to efficiently tackle the cross-domain distribution shift at test time for medical images from different institu…
Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion
Cheng Chen, Qi Dou, Yueming Jin +3
Accurate medical image segmentation commonly requires effective learning of the complementary information from multimodal data. However, in clinical practice, we often encounter th…
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation
Cheng Chen, Qi Dou, Hao Chen +2
This paper presents a novel unsupervised domain adaptation framework, called Synergistic Image and Feature Adaptation (SIFA), to effectively tackle the problem of domain shift. Dom…
Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation
Cheng Chen, Qi Dou, Hao Chen +1
In spite of the compelling achievements that deep neural networks (DNNs) have made in medical image computing, these deep models often suffer from degraded performance when being a…