activity
20172023
most citedOn Geometric Structure of Activation Spaces in Neural Networks

5 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2023

GaitASMS: Gait Recognition by Adaptive Structured Spatial Representation and Multi-Scale Temporal Aggregation

Yan Sun, Hu Long, Xueling Feng +1

Gait recognition is one of the most promising video-based biometric technologies. The edge of silhouettes and motion are the most informative feature and previous studies have expl…

cs.LG2019★ 5 cited

On Geometric Structure of Activation Spaces in Neural Networks

Yuting Jia, Haiwen Wang, Shuo Shao +3

In this paper, we investigate the geometric structure of activation spaces of fully connected layers in neural networks and then show applications of this study. We propose an effi…

cs.CV2018

Knowledge-based Fully Convolutional Network and Its Application in Segmentation of Lung CT Images

Tao Yu, Yu Qiao, Huan Long

A variety of deep neural networks have been applied in medical image segmentation and achieve good performance. Unlike natural images, medical images of the same imaging modality a…

cs.LG2018

Curvature-based Comparison of Two Neural Networks

Tao Yu, Huan Long, John E. Hopcroft

In this paper we show the similarities and differences of two deep neural networks by comparing the manifolds composed of activation vectors in each fully connected layer of them.…

cs.CV2017★ 2 cited

The Local Dimension of Deep Manifold

Mengxiao Zhang, Wangquan Wu, Yanren Zhang +4

Based on our observation that there exists a dramatic drop for the singular values of the fully connected layers or a single feature map of the convolutional layer, and that the di…