57 citations · 100 across the 4 of their papers we have counts for
6 papers
Dispensed Transformer Network for Unsupervised Domain Adaptation
Yunxiang Li, Jingxiong Li, Ruilong Dan +10
Accurate segmentation is a crucial step in medical image analysis and applying supervised machine learning to segment the organs or lesions has been substantiated effective. Howeve…
GT U-Net: A U-Net Like Group Transformer Network for Tooth Root Segmentation
Yunxiang Li, Shuai Wang, Jun Wang +5
To achieve an accurate assessment of root canal therapy, a fundamental step is to perform tooth root segmentation on oral X-ray images, in that the position of tooth root boundary…
AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy
Yunxiang Li, Guodong Zeng, Yifan Zhang +10
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results wi…
High-Resolution Segmentation of Tooth Root Fuzzy Edge Based on Polynomial Curve Fitting with Landmark Detection
Yunxiang Li, Yifan Zhang, Yaqi Wang +7
As the most economical and routine auxiliary examination in the diagnosis of root canal treatment, oral X-ray has been widely used by stomatologists. It is still challenging to seg…
A cascade network for Detecting COVID-19 using chest x-rays
Dailin Lv, Wuteng Qi, Yunxiang Li +2
The worldwide spread of pneumonia caused by a novel coronavirus poses an unprecedented challenge to the world's medical resources and prevention and control measures. Covid-19 atta…
Efficient and Robust Reinforcement Learning with Uncertainty-based Value Expansion
Bo Zhou, Hongsheng Zeng, Fan Wang +2
By integrating dynamics models into model-free reinforcement learning (RL) methods, model-based value expansion (MVE) algorithms have shown a significant advantage in sample effici…