1.3k citations · 2.6k across the 51 of their papers we have counts for
7 papers · 1 filter
Deep Distance Transform for Tubular Structure Segmentation in CT Scans
Yan Wang, Xu Wei, Fengze Liu +5
Tubular structure segmentation in medical images, e.g., segmenting vessels in CT scans, serves as a vital step in the use of computers to aid in screening early stages of related d…
Rethinking Normalization and Elimination Singularity in Neural Networks
Siyuan Qiao, Huiyu Wang, Chenxi Liu +2
In this paper, we study normalization methods for neural networks from the perspective of elimination singularity. Elimination singularities correspond to the points on the trainin…
Deeply Shape-guided Cascade for Instance Segmentation
Hao Ding, Siyuan Qiao, Alan Yuille +1
The key to a successful cascade architecture for precise instance segmentation is to fully leverage the relationship between bounding box detection and mask segmentation across mul…
Deep Differentiable Random Forests for Age Estimation
Wei Shen, Yilu Guo, Yan Wang +3
Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feat…
Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks
Wei Shen, Fei Li, Rujie Liu
Training convolutional neural networks for image classification tasks usually causes information loss. Although most of the time the information lost is redundant with respect to t…
Learning from Adversarial Features for Few-Shot Classification
Wei Shen, Ziqiang Shi, Jun Sun
Many recent few-shot learning methods concentrate on designing novel model architectures. In this paper, we instead show that with a simple backbone convolutional network we can ev…