Corpus ID: 140117854

Efficient Neural Architecture Search on Low-Dimensional Data for OCT Image Segmentation

@article{Gessert2019EfficientNA,
  title={Efficient Neural Architecture Search on Low-Dimensional Data for OCT Image Segmentation},
  author={N. Gessert and A. Schlaefer},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.02590}
}
  • N. Gessert, A. Schlaefer
  • Published 2019
  • Computer Science, Engineering
  • ArXiv
  • Typically, deep learning architectures are handcrafted for their respective learning problem. As an alternative, neural architecture search (NAS) has been proposed where the architecture's structure is learned in an additional optimization step. For the medical imaging domain, this approach is very promising as there are diverse problems and imaging modalities that require architecture design. However, NAS is very time-consuming and medical learning problems often involve high-dimensional data… CONTINUE READING
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