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Topological Data Analysis: potential applications to computer vision

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Topological Data Analysis quantifies hidden topological structures in big raw noisy data. The flagship tool (persistent homology) summarises the underlying structure across all scales. The stability result says that such a summary (persistence diagram) is robust to noise. We shall review potential approaches to combine topological data analysis and machine learning for practical problems in computer vision.

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