44 citations · 87 across the 10 of their papers we have counts for
4 papers · 1 filter
Early Stopping for Deep Image Prior
Hengkang Wang, Taihui Li, Zhong Zhuang +3
Deep image prior (DIP) and its variants have showed remarkable potential for solving inverse problems in computer vision, without any extra training data. Practical DIP models are…
Self-Validation: Early Stopping for Single-Instance Deep Generative Priors
Taihui Li, Zhong Zhuang, Hengyue Liang +3
Recent works have shown the surprising effectiveness of deep generative models in solving numerous image reconstruction (IR) tasks, even without training data. We call these models…
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Ju Sun, Le Peng, Taihui Li +14
Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate cli…
Rethinking Transfer Learning for Medical Image Classification
Le Peng, Hengyue Liang, Gaoxiang Luo +2
Transfer learning (TL) from pretrained deep models is a standard practice in modern medical image classification (MIC). However, what levels of features to be reused are problem-de…