Adversarial-Deep-Learning / Adversarial-Deep-Learning/code-soup

Non targeted One Pixel Attack on random 500 samples

Abierto
#78 2 comentarios 0 reacciones 0 asignados Ver en GitHub
good first issue Priority:Medium Tutorials
Lenguaje dominante
Jupyter Notebook
Estrellas
17
Forks
17
Métricas de merge de PR
Sin PR fusionados en 30 d

Descripción

This will be one of the tutorials for One Pixel Attack using VGG16 and CIFAR10 (open to discussion if difficult). Try to include the visualizations in original paper. [Link](https://arxiv.org/pdf/1710.08864.pdf)

The following is the minimum requirement:-

- [ ] attack on 500 random samples
- [ ] Attack using 1/3/5 Pixel(s)
- [ ] Accuracy and Confidence analysis
- [ ] Pre and Post attack Image visualizations

Guía de contribución

Abrir la guía de contribución

Evaluación

Este issue todavía no se ha evaluado.

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.