• DOI:10.1073/pnas.1907377117
Corpus ID: 61153569

On instabilities of deep learning in image reconstruction and the potential costs of AI

@article{Antun2020OnIO,
  title={On instabilities of deep learning in image reconstruction and the potential costs of AI},
  author={Vegard Antun and Francesco Renna and C. Poon and B. Adcock and A. Hansen},
  journal={Proceedings of the National Academy of Sciences},
  year={2020},
  volume={117},
  pages={30088 - 30095}
}

Vegard Antun, Francesco Renna, +2 authors A. Hansen

Published 2020

Computer Science, Medicine

Proceedings of the National Academy of Sciences

Deep learning, due to its unprecedented success in tasks such as image classification, has emerged as a new tool in image reconstruction with potential to change the field. In this paper, we demonstrate a crucial phenomenon: Deep learning typically yields unstable methods for image reconstruction. The instabilities usually occur in several forms: 1) Certain tiny, almost undetectable perturbations, both in the image and sampling domain, may result in severe artefacts in the reconstruction; 2) a… CONTINUE READING

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