This repository presents a compelling case study on the vulnerability of neural networks to targeted deceptions. By using a Convolutional Neural Network (CNN) trained on the MNIST dataset, we demonstrate how a well-trained model can be deceived into misclassifying manipulated input with high confidence.
active 2023-12-27 → 2023-12-28 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 2 days from 2023-12-27 to 2023-12-28. Pushes: 14 total, peak 8 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
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- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| mertkipcak | 16 | 14 | 2 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.