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. Live Demo For a live demo,

visit: http://poloclub.github.io/cnn-explainer/

Running Locally Clone or download this repository: git clone git@github.com:poloclub/cnn-explainer.git # use degit if you don't want to download commit histories degit poloclub/cnn-explainer Install the dependencies: npm install Then run CNN Explainer: npm run dev Navigate to localhost:5000.

you should see CNN Explainer running in your broswer :) To see how we trained the CNN, visit the directory ./tiny-vgg/. Credits 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. Citatio

@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]} }