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# Fooling Code |
# Fooling Code |
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This is the code base used to reproduce the "fooling" images in the paper: |
This is the code base used to reproduce the "fooling" images in the paper: |
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[Nguyen A](http://anhnguyen.me), [Yosinski J](http://yosinski.com/), [Clune J](http://jeffclune.com). ["Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"](http://arxiv.org/abs/1412.1897). In Computer Vision and Pattern Recognition (CVPR '15), IEEE, 2015. |
[Nguyen A](http://anhnguyen.me), [Yosinski J](http://yosinski.com/), [Clune J](http://jeffclune.com). ["Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"](http://arxiv.org/abs/1412.1897). In Computer Vision and Pattern Recognition (CVPR '15), IEEE, 2015. |
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**If you use this software in an academic article, please cite:** |
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@inproceedings{nguyen2015deep, |
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title={Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images}, |
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author={Nguyen, Anh and Yosinski, Jason and Clune, Jeff}, |
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booktitle={Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on}, |
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year={2015}, |
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organization={IEEE} |
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} |
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For more information regarding the paper, please visit www.evolvingai.org/fooling |
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## Requirements |
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This is an installation process that requires two main software packages (included in this package): |
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1. Caffe: http://caffe.berkeleyvision.org |
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* Our libraries installed to work with Caffe |
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* Cuda 6.0 |
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* Boost 1.52 |
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* g++ 4.6 |
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* Use the provided scripts to download the correct version of Caffe for your experiments. |
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* `./download_caffe_evolutionary_algorithm.sh` Caffe version for EA experiments |
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* `./download_caffe_gradient_ascent.sh` Caffe version for gradient ascent experiments |
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2. Sferes: https://github.com/jbmouret/sferes2 |
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* Our libraries installed to work with Sferes |
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* OpenCV 2.4.10 |
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* Boost 1.52 |
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* g++ 4.9 (a C++ compiler compatible with C++11 standard) |
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* Use the provided script `./download_sferes.sh` to download the correct version of Sferes. |
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Note: These are patched versions of the two frameworks with our additional work necessary to produce the images as in the paper. They are not the same as their master branches. |
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