56 citations · 123 across the 22 of their papers we have counts for
10 papers · 1 filter
Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation
Dewen Zeng, Xinrong Hu, Yu-Jen Chen +3
Weakly supervised semantic segmentation (WSSS) methods using class labels often rely on class activation maps (CAMs) to localize objects. However, traditional CAM-based methods str…
Enhancing 3D Transformer Segmentation Model for Medical Image with Token-level Representation Learning
Xinrong Hu, Dewen Zeng, Yawen Wu +2
In the field of medical images, although various works find Swin Transformer has promising effectiveness on pixelwise dense prediction, whether pre-training these models without us…
Contrastive Learning with Synthetic Positives
Dewen Zeng, Yawen Wu, Xinrong Hu +2
Contrastive learning with the nearest neighbor has proved to be one of the most efficient self-supervised learning (SSL) techniques by utilizing the similarity of multiple instance…
Achieve Fairness without Demographics for Dermatological Disease Diagnosis
Ching-Hao Chiu, Yu-Jen Chen, Yawen Wu +2
In medical image diagnosis, fairness has become increasingly crucial. Without bias mitigation, deploying unfair AI would harm the interests of the underprivileged population and po…
Additional Positive Enables Better Representation Learning for Medical Images
Dewen Zeng, Yawen Wu, Xinrong Hu +3
This paper presents a new way to identify additional positive pairs for BYOL, a state-of-the-art (SOTA) self-supervised learning framework, to improve its representation learning a…
Self-supervised On-device Federated Learning from Unlabeled Streams
Jiahe Shi, Yawen Wu, Dewen Zeng +3
The ubiquity of edge devices has led to a growing amount of unlabeled data produced at the edge. Deep learning models deployed on edge devices are required to learn from these unla…
Enabling Weakly-Supervised Temporal Action Localization from On-Device Learning of the Video Stream
Yue Tang, Yawen Wu, Peipei Zhou +1
Detecting actions in videos have been widely applied in on-device applications. Practical on-device videos are always untrimmed with both action and background. It is desirable for…
Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization
Gelei Xu, Yawen Wu, Jingtong Hu +1
Dermatological diseases pose a major threat to the global health, affecting almost one-third of the world's population. Various studies have demonstrated that early diagnosis and i…
Synthetic Data Can Also Teach: Synthesizing Effective Data for Unsupervised Visual Representation Learning
Yawen Wu, Zhepeng Wang, Dewen Zeng +2
Contrastive learning (CL), a self-supervised learning approach, can effectively learn visual representations from unlabeled data. Given the CL training data, generative models can…
Positional Contrastive Learning for Volumetric Medical Image Segmentation
Dewen Zeng, Yawen Wu, Xinrong Hu +6
The success of deep learning heavily depends on the availability of large labeled training sets. However, it is hard to get large labeled datasets in medical image domain because o…