13 citations · 14 across the 5 of their papers we have counts for
5 papers
Discrepancy-based Active Learning for Weakly Supervised Bleeding Segmentation in Wireless Capsule Endoscopy Images
Fan Bai, Xiaohan Xing, Yutian Shen +2
Weakly supervised methods, such as class activation maps (CAM) based, have been applied to achieve bleeding segmentation with low annotation efforts in Wireless Capsule Endoscopy (…
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation
Fan Bai, Ke Yan, Xiaoyu Bai +6
Medical image analysis using deep learning is often challenged by limited labeled data and high annotation costs. Fine-tuning the entire network in label-limited scenarios can lead…
Deep Reinforcement Learning-Based Control for Stomach Coverage Scanning of Wireless Capsule Endoscopy
Yameng Zhang, Long Bai, Li Liu +2
Due to its non-invasive and painless characteristics, wireless capsule endoscopy has become the new gold standard for assessing gastrointestinal disorders. Omissions, however, coul…
Style Transfer Enabled Sim2Real Framework for Efficient Learning of Robotic Ultrasound Image Analysis Using Simulated Data
Keyu Li, Xinyu Mao, Chengwei Ye +3
Robotic ultrasound (US) systems have shown great potential to make US examinations easier and more accurate. Recently, various machine learning techniques have been proposed to rea…
Direct Visual Servoing Based on Discrete Orthogonal Moments
Yuhan Chen, Max Q. -H. Meng, Li Liu
This paper proposes a new approach to achieve direct visual servoing (DVS) based on discrete orthogonal moments (DOMs). DVS is performed in such a way that the extraction of geomet…