Unsupervised-Anomaly-Detection-with-Generative-Adversarial-Networks

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Anomaly detection using GANs

The goal of this project is be able to detect anomolies using GANs based on Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

Dataset

we are using MIAS dataset http://peipa.essex.ac.uk/info/mias.html

Architecture

Our code is based on DCGAN from this wonderful repo https://github.com/carpedm20/DCGAN-tensorflow

Results

• TODO

How to run

• TODO

Contributors

• Ahmed Ayad
• M.Tarek Shaban - @XtarX
• Wassim Gabriel - @wassimG

To Do

• [ ] Complete Readme.
• [ ] Evaluate on 128x128 patches.

License

Apache License 2.0