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cs.CV2025
Challenges in 3D Data Synthesis for Training Neural Networks on Topological Features
Dylan Peek, Matthew P. Skerritt, Siddharth Pritam +1
Topological Data Analysis (TDA) involves techniques of analyzing the underlying structure and connectivity of data. However, traditional methods like persistent homology can be com…
cs.CV2025
Noise-Robust Topology Estimation of 2D Image Data via Neural Networks and Persistent Homology
Dylan Peek, Matthew P. Skerritt, Stephan Chalup
Persistent Homology (PH) and Artificial Neural Networks (ANNs) offer contrasting approaches to inferring topological structure from data. In this study, we examine the noise robust…
cs.CV2024
Generating Topologically and Geometrically Diverse Manifold Data in Dimensions Four and Below
Khalil Mathieu Hannouch, Stephan Chalup
Understanding the topological characteristics of data is important to many areas of research. Recent work has demonstrated that synthetic 4D image-type data can be useful to train…