https://github.com/red-rapious/adversarial-attacks
Report, slides and code of our presentation about Adversarial Attacks for the class "Introduction to Computer Vision"
https://github.com/red-rapious/adversarial-attacks
adversarial-attacks adversarial-defense computer-vision deep-learning
Last synced: 8 months ago
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Report, slides and code of our presentation about Adversarial Attacks for the class "Introduction to Computer Vision"
- Host: GitHub
- URL: https://github.com/red-rapious/adversarial-attacks
- Owner: Red-Rapious
- Created: 2024-12-18T10:53:47.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-19T12:18:40.000Z (over 1 year ago)
- Last Synced: 2025-01-19T13:19:30.949Z (over 1 year ago)
- Topics: adversarial-attacks, adversarial-defense, computer-vision, deep-learning
- Language: TeX
- Homepage:
- Size: 20.9 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Adversarial-Attacks
Report, slides and code of our presentation about Adversarial Attacks for the class "Introduction to Computer Vision".
## Files description
- `report/report.pdf`: report of the presentation.
- `slides/slides.pdf`: slides of the presentation.
- `code/fgsm.ipynb`: implementation of the Fast Gradient Sign Method (FGSM) attack.
- `code/defence-adversarial-training.ipynb`: implementation of adversarial training as a defense mechanism.
- `code/null-labeling.ipynb`: implementation of null-labeling as a defense mechanism.