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adversarial-nn

Python Anaconda Jupyter Notebook PyTorch NumPy scikit-learn

This project was executed as a school assignment at the University of Twente. In this project a basic CNN model (created by ourselves) and the ResNet-50 model are trained upon the Fashion-MNIST dataset whereafter different adversial attacks and defences are applied to look at their impact on the classification accuracy.

Project Overview

  • School: University of Twente
  • Course: Deep Learning - From Theory to Practice
  • Assignment Type: Topic wiht open implementation
  • Group Size: 4

Execution

All code with explanation can be found in the main.ipynb notebook. Trained models are saved in the model directory and figures are saved in the results dictionary.

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