https://github.com/poloclub/cnn-explainer

Learning Convolutional Neural Networks with Interactive Visualization.
https://github.com/poloclub/cnn-explainer

deep-learning interactive-visualizations machine-learning visual-learning visualization

Last synced: 4 days ago
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Learning Convolutional Neural Networks with Interactive Visualization.

• Host: GitHub
• URL: https://github.com/poloclub/cnn-explainer
• Owner: poloclub
• License: mit
• Created: 2019-11-03T23:15:24.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2023-10-14T15:56:25.000Z (about 1 year ago)
• Last Synced: 2024-12-10T15:36:12.551Z (11 days ago)
• Topics: deep-learning, interactive-visualizations, machine-learning, visual-learning, visualization
• Language: JavaScript
• Homepage: https://poloclub.github.io/cnn-explainer/
• Size: 86.2 MB
• Stars: 8,184
• Watchers: 165
• Forks: 1,239
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# CNN Explainer

An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs)

[![build](https://github.com/poloclub/cnn-explainer/workflows/build/badge.svg)](https://github.com/poloclub/cnn-explainer/actions)

[![arxiv badge](https://img.shields.io/badge/arXiv-2004.15004-red)](http://arxiv.org/abs/2004.15004)

[![DOI:10.1109/TVCG.2020.3030418](https://img.shields.io/badge/DOI-10.1109/TVCG.2020.3030418-blue)](https://doi.org/10.1109/TVCG.2020.3030418)



For more information, check out our manuscript:

[**CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization**](https://arxiv.org/abs/2004.15004).

Wang, Zijie J., Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, and Duen Horng Chau.

*IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020.*

## Live Demo

For a live demo, visit: http://poloclub.github.io/cnn-explainer/

## Running Locally

Clone or download this repository:

```bash

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:

```bash

npm install

```

Then run CNN Explainer:

```bash

npm run dev

```

Navigate to [localhost:3000](https://localhost:3000). You should see CNN Explainer running in your broswer :)

To see how we trained the CNN, visit the directory [`./tiny-vgg/`](tiny-vgg).

If you want to use CNN Explainer with your own CNN model or image classes, see [#8](/../../issues/8) and [#14](/../../issues/14).

## 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](https://www.linkedin.com/in/anmolchhabria),

[Kaan Sancak](https://kaansancak.com),

[Kantwon Rogers](https://www.kantwon.com), and the

[Georgia Tech Visualization Lab](http://vis.gatech.edu)

for their support and constructive feedback.

## Citation

```bibTeX

@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},

  journal={IEEE Transactions on Visualization and Computer Graphics (TVCG)},

  year={2020},

  publisher={IEEE}

}

```

## License

The software is available under the [MIT License](https://github.com/poloclub/cnn-explainer/blob/master/LICENSE).

## Contact

If you have any questions, feel free to [open an issue](https://github.com/poloclub/cnn-explainer/issues/new/choose) or contact [Jay Wang](https://zijie.wang).