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RanTaimu / Adversarial-Transformation-Network

Licence: GPL-3.0 license
A simple implement of an Adversarial Autoencoding ATN(AAE ATN)

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Adversarial Transformation Network(ATN)

Introduction

A simple implement of an Adversarial Autoencoding ATN(AAE ATN) proposed in Adversarial Transformation Networks: Learning to Generate Adversarial Examples using tensorflow.

Requirements

python 3.5

tensorflow 1.1.0

matplotlib (for result visualizing)

Usage

You can test with my trained model:

python atn.py

If you want to train by yourself:

python atn.py --train

Result

Here are some visualized samples:

result

Before attack, the accuracy of the target cnn network is 0.9902, and it becomes 0.2773 after attack.

The result is not good enough, so WELCOME CONTRIBUTION !!!

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