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: 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-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/. 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.