/DeepLearning-SeGAN-Segmentation

This contains an implementation of the SeGAN model for semantic segmentation introduced in https://arxiv.org/pdf/1703.10239.pdf

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DeepLearning SeGAN Segmentation

This contains an implementation of the SeGAN model for semantic segmentation introduced in https://arxiv.org/pdf/1703.10239.pdf

The model serves for semantic segmenation of image data and the authors have demonstrated its utility on cranial MRT images.

A summary of the model architecture from the paper is shown below SegAN

Dependencies

  • Python 3.6
  • Numpy
  • Keras 2.0
  • Tensorflow >= 1.x
  • TQDM (optional)

This work was inspired by Xue et al. as well as the excellent "Deep Learning for coders" tought by Jeremy Howard and Rachel Thomas in their MOOC