Dark soliton detection using persistent homology.

@article{Leykam2022DarkSD,
  title={Dark soliton detection using persistent homology.},
  author={Daniel Leykam and Irving Rond{\'o}n and D. G. Angelakis},
  journal={Chaos},
  year={2022},
  volume={32 7},
  pages={
          073133
        }
}
Classifying images often requires manual identification of qualitative features. Machine learning approaches including convolutional neural networks can achieve accuracy comparable to human classifiers but require extensive data and computational resources to train. We show how a topological data analysis technique, persistent homology, can be used to rapidly and reliably identify qualitative features in experimental image data. The identified features can be used as inputs to simple supervised… 

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