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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.CV2023
Synthetic Data Generation and Deep Learning for the Topological Analysis of 3D Data
Dylan Peek, Matt P. Skerritt, Stephan Chalup
This research uses deep learning to estimate the topology of manifolds represented by sparse, unordered point cloud scenes in 3D. A new labelled dataset was synthesised to train ne…