A Sheaf and Topology Approach to Generating Local Branch Numbers in Digital Images

27 November 2020

Papers citing "A Sheaf and Topology Approach to Generating Local Branch Numbers in Digital Images"

8 / 8 papers shown

Title
PI-Net: A Deep Learning Approach to Extract Topological Persistence Images Anirudh Som Hongjun Choi Karthikeyan N. Ramamurthy M. Buman Pavan Turaga 3DH 38 30 0 05 Jun 2019
Kernel method for persistence diagrams via kernel embedding and weight factor G. Kusano Kenji Fukumizu Y. Hiraoka 30 83 0 12 Jun 2017
The accumulated persistence function, a new useful functional summary statistic for topological data analysis, with a view to brain artery trees and spatial point process applications C. Biscio Jesper Møller 100 61 0 02 Nov 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.4K 192,638 0 10 Dec 2015
Sliced Wasserstein Kernels for Probability Distributions Soheil Kolouri Yang Zou Gustavo K. Rohde 34 159 0 10 Nov 2015
Persistence Images: A Stable Vector Representation of Persistent Homology Henry Adams Sofya Chepushtanova Tegan H. Emerson Eric M. Hanson Michael Kirby Francis C. Motta R. Neville C. Peterson Patrick D. Shipman Lori Ziegelmeier 54 674 0 22 Jul 2015
Persistent Homology in Sparse Regression and its Application to Brain Morphometry M. Chung J. Hanson Jieping Ye R. Davidson S. Pollak 61 68 0 31 Aug 2014
Statistical topological data analysis using persistence landscapes Peter Bubenik 134 851 0 27 Jul 2012