870 citations · 1.7k across the 3 of their papers we have counts for
3 papers
cs.CV2022
Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation
Wenyu Zhang, Li Shen, Chuan-Sheng Foo
Source-free domain adaptation (SFDA) aims to adapt a source model trained on a fully-labeled source domain to an unlabeled target domain. Large-data pre-trained networks are used t…
cs.CV2017★ 870 cited
End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design
Li Shen
We develop an end-to-end training algorithm for whole-image breast cancer diagnosis based on mammograms. It requires lesion annotations only at the first stage of training. After t…
cs.CV2017★ 870 cited
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
Li Shen, Laurie R. Margolies, Joseph H. Rothstein +3
The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep l…