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Fully Convolutional Fractional Scaling

Neural and Evolutionary Computing 2022-03-22 v1 Machine Learning
Authors: Michael Soloveitchik , Michael Werman
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Abstract

We introduce a fully convolutional fractional scaling component, FCFS. Fully convolutional networks can be applied to any size input and previously did not support non-integer scaling. Our architecture is simple with an efficient single layer implementation. Examples and code implementations of three common scaling methods are published.

Keywords

fingerprint recognition nonnegative matrix factorization

Cite

@article{arxiv.2203.10670,
  title  = {Fully Convolutional Fractional Scaling},
  author = {Michael Soloveitchik and Michael Werman},
  journal= {arXiv preprint arXiv:2203.10670},
  year   = {2022}
}

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