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SNGAC

Style Neutralization Generative Adversarial Classifier

It is the basic code implementation of the paper Style Neutralization Generative Adversarial Classifier in the 9th International Conference of Brain-Inspired Congitive System (BICS-2018), authored by Haochuan JIANG, Kaizhu HUANG, Rui ZHANG and Amir HUSSAIN from the Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, SIP, Suzhou, P.R.China / the Division of Computing Science and Maths, School of Natural Sciences, University of Stirling, Stirling, Scotland, U.K.

The code is written based on the Tensorflow Deep Learning Library (r1.90, python=2.7). Additional python dependencies are as follows: pip install matplotlib scipy imageio

It is recommended that the python environment is installed on the Anaconda framework.

Citation: @inproceedings{jiang2018style, title={Style Neutralization Generative Adversarial Classifier}, author={Jiang, Haochuan and Huang, Kaizhu and Zhang, Rui and Hussain, Amir}, booktitle={International Conference on Brain Inspired Cognitive Systems}, pages={3--13}, year={2018}, organization={Springer} }

@article{jiang2019style, title={Style-Neutralized Pattern Classification Based on Adversarially Trained Upgraded U-Net}, author={Jiang, Haochuan and Huang, Kaizhu and Zhang, Rui and Hussain, Amir}, journal={Cognitive Computation}, pages={1--14}, year={2019}, publisher={Springer} }

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