PI-Net: A Deep Learning Approach to Extract Topological Persistence Images

Abstract
Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for machine learning and computer vision applications. This is greatly attributed to the robustness topological representations provide against different types of physical nuisance variables seen in real-world data, such as view-point, illumination, and more. However, key bottlenecks to their...
Paper Details
Title
PI-Net: A Deep Learning Approach to Extract Topological Persistence Images
Published Date
Jun 5, 2019
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