Multiscale anomaly detection using diffusion maps and saliency score

@article{Mishne2014MultiscaleAD,
  title={Multiscale anomaly detection using diffusion maps and saliency score},
  author={Gal Mishne and Israel Cohen},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={2823-2827}
}
Recently, we presented a multiscale approach to anomaly detection in images, combining diffusion maps for dimensionality reduction and a nearest-neighbor-based anomaly score in the reduced dimension. When applying diffusion maps to images, usually a process of sampling and out-of-sample extension is used, which has limitations in regards to anomaly detection. To overcome the limitations, a multiscale approach was proposed, which drives the sampling process to ensure separability of the anomaly… CONTINUE READING

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