Semantic Fusion GAN for semi-supervised image classification
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tflib
README.md
file_reader.m
sfgan_train_eval.py

README.md

SFGAN: Semantic Fusion GAN for semi-supervised learning

Code for paper Semantic-Fusion GANs for Semi-Supervised Satellite Image Classification accepted in the International Conference on Image Processing (ICIP) to be held in Athens, Greece in October, 2018.

Code is available now.

Requirements

  1. Tensorflow 1.5
  2. Python 3.5

Instructions

  1. First download the EuroSAT data set and extract the images.
  2. Run the file_reader.m to convert the images into a .mat file. This will be used as input for training the network.
  3. Run sfgan_train_eval.py to train the network.

N.B. Python 3 is recommended for running this code as the batching gives errornoues results with lower versions of Python. Haven't tried with other versions of Tensorflow.

Citation

If you use this code for your research, please cite our paper

@inproceedings{roy2018semantic,
  title={Semantic-Fusion Gans for Semi-Supervised Satellite Image Classification},
  author={Roy, Subhankar and Sangineto, Enver and Sebe, Nicu and Demir, Beg{\"u}m},
  booktitle={2018 25th IEEE International Conference on Image Processing (ICIP)},
  pages={684--688},
  year={2018},
  organization={IEEE}
}

A commented version of the code will be updated soon.