13 citations · 24 across the 5 of their papers we have counts for
7 papers
Globally Optimal Segmentation of Mutually Interacting Surfaces using Deep Learning
Hui Xie, Zhe Pan, Leixin Zhou +5
Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary and mutual influence between adjacent ob…
Globally Optimal Surface Segmentation using Deep Learning with Learnable Smoothness Priors
Leixin Zhou, Xiaodong Wu
Automated surface segmentation is important and challenging in many medical image analysis applications. Recent deep learning based methods have been developed for various object s…
Unsupervised anomaly localization using VAE and beta-VAE
Leixin Zhou, Wenxiang Deng, Xiaodong Wu
Variational Auto-Encoders (VAEs) have shown great potential in the unsupervised learning of data distributions. An VAE trained on normal images is expected to only be able to recon…
Deep Neural Networks for Surface Segmentation Meet Conditional Random Fields
Leixin Zhou, Zisha Zhong, Abhay Shah +3
Automated surface segmentation is important and challenging in many medical image analysis applications. Recent deep learning based methods have been developed for various object s…
Trust but Verify: An Information-Theoretic Explanation for the Adversarial Fragility of Machine Learning Systems, and a General Defense against Adversarial Attacks
Jirong Yi, Hui Xie, Leixin Zhou +3
Deep-learning based classification algorithms have been shown to be susceptible to adversarial attacks: minor changes to the input of classifiers can dramatically change their outp…
Robust Image Segmentation Quality Assessment
Leixin Zhou, Wenxiang Deng, Xiaodong Wu
Deep learning based image segmentation methods have achieved great success, even having human-level accuracy in some applications. However, due to the black box nature of deep lear…