85 citations · 273 across the 17 of their papers we have counts for
17 papers
CAMANet: Class Activation Map Guided Attention Network for Radiology Report Generation
Jun Wang, Abhir Bhalerao, Terry Yin +2
Radiology report generation (RRG) has gained increasing research attention because of its huge potential to mitigate medical resource shortages and aid the process of disease decis…
Perceptual Learned Source-Channel Coding for High-Fidelity Image Semantic Transmission
Jun Wang, Sixian Wang, Jincheng Dai +3
As one novel approach to realize end-to-end wireless image semantic transmission, deep learning-based joint source-channel coding (deep JSCC) method is emerging in both deep learni…
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Tianyang Hu, Jun Wang, Wenjia Wang +1
Deep learning has achieved many breakthroughs in modern classification tasks. Numerous architectures have been proposed for different data structures but when it comes to the loss…
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…
PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refinement
Jun Wang, Hefeng Zhou, Xiaohan Yu
Current state-of-the-art weakly supervised object detection (WSOD) studies mainly follow a two-stage training strategy which integrates a fully supervised detector (FSD) with a pur…