13 citations · 15 across the 4 of their papers we have counts for
4 papers
Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms
Xuxin Chen, Ke Zhang, Neman Abdoli +5
Deep convolutional neural networks (CNNs) have been widely used in various medical imaging tasks. However, due to the intrinsic locality of convolution operation, CNNs generally ca…
Virtual Adversarial Training for Semi-supervised Breast Mass Classification
Xuxin Chen, Ximin Wang, Ke Zhang +7
This study aims to develop a novel computer-aided diagnosis (CAD) scheme for mammographic breast mass classification using semi-supervised learning. Although supervised deep learni…
Sound Event Detection Transformer: An Event-based End-to-End Model for Sound Event Detection
Zhirong Ye, Xiangdong Wang, Hong Liu +4
Sound event detection (SED) has gained increasing attention with its wide application in surveillance, video indexing, etc. Existing models in SED mainly generate frame-level predi…
Multi-Branch Learning for Weakly-Labeled Sound Event Detection
Yuxin Huang, Xiangdong Wang, Liwei Lin +2
There are two sub-tasks implied in the weakly-supervised SED: audio tagging and event boundary detection. Current methods which combine multi-task learning with SED requires annota…