An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs)
For more information, check out our manuscript:
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization. Wang, Zijie J., Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, and Duen Horng Chau. arXiv preprint 2020. arXiv:2004.15004.
For a live demo, visit: http:https://poloclub.github.io/cnn-explainer/
Clone or download this repository:
git clone [email protected]:poloclub/cnn-explainer.git
# use degit if you don't want to download commit histories
degit poloclub/cnn-explainerInstall the dependencies:
npm installThen run CNN Explainer:
npm run devNavigate to localhost:5000. You should see CNN Explainer running in your broswer :)
To see how we trained the CNN, visit the directory ./tiny-vgg/.
If you want to use CNN Explainer with your own CNN model or image classes, see #8 and #14.
CNN Explainer was created by Jay Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, and Polo Chau, which was the result of a research collaboration between Georgia Tech and Oregon State.
We thank Anmol Chhabria, Kaan Sancak, Kantwon Rogers, and the Georgia Tech Visualization Lab for their support and constructive feedback.
@article{wangCNNExplainerLearning2020,
title = {{{CNN Explainer}}: {{Learning Convolutional Neural Networks}} with {{Interactive Visualization}}},
shorttitle = {{{CNN Explainer}}},
author = {Wang, Zijie J. and Turko, Robert and Shaikh, Omar and Park, Haekyu and Das, Nilaksh and Hohman, Fred and Kahng, Minsuk and Chau, Duen Horng},
year = {2020},
month = apr,
archivePrefix = {arXiv},
eprint = {2004.15004},
eprinttype = {arxiv},
journal = {arXiv:2004.15004 [cs]}
}The software is available under the MIT License.
If you have any questions, feel free to open an issue or contact Jay Wang.
