- Our paper is accepted to IEEE ICIP 2018.
- Code and Tensorflow model will be released from this page very soon.
Please cite the following papers:
[1] Savas Ozkan and Gozde Bozdagi Akar, Deep Spectral Convolution Network for HyperSpectral Unmixing, IEEE International Conference on Image Processing, 2018:
[2] Savas Ozkan and Gozde Bozdagi Akar, Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember Uncertainty, arXiv:1808.01104, 2018:
@article{ozkan18dscn,
title={Deep Spectral Convolution Network for HyperSpectral Unmixing},
author={Ozkan, Savas and Akar, Gozde Bozdagi},
journal={IEEE International Conference on Image Processing},
year={2018},
}
@article{ozkan2018improved,
title={Improved Deep Spectral Convolution Network For Hyperspectral Unmixing With Multinomial Mixture Kernel and Endmember Uncertainty},
author={Ozkan, Savas and Akar, Gozde Bozdagi},
journal={arXiv preprint arXiv:1808.01104},
year={2018}
}
@article{ozkan2020su,
title={Spectral Unmixing With Multinomial Mixture Kernel and Wasserstein Generative Adversarial Loss},
author={Ozkan, Savas and Akar, Gozde Bozdagi},
journal={AI for Earth Sciences Workshop at NeurIPS 2020},
year={2020}
}