utkuozbulak/imagenet-adversarial-image-evaluation

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utkuozbulak/imagenet-adversarial-image-evaluation

utkuozbulak

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Code and some materials from the papers "Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks" (BMVC 2021) and "Evaluating Adversarial Attacks on ImageNet:A Reality Check on Misclassification Classes" (NeurIPS 2021, Workshop track).

pytorch-cnn-visualizations

Pytorch implementation of convolutional neural network visualization techniques

pytorch-custom-dataset-examples

Some custom dataset examples for PyTorch

pytorch-cnn-adversarial-attacks

Pytorch implementation of convolutional neural network adversarial attack techniques

unsupervised-learning-document-clustering

Document clustering and topic modelling with Python

adaptive-segmentation-mask-attack

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

facial-expression-recognition

Predicting facial expressions with machine learning algorithms

singular-value-decomposition-on-images

Singular Value Decomposition on rgb and grayscale images

UCL-DSSC-Hackaton

Winning project of 2017 University College London Data Science Hackathon

Jupyter Notebook

regional-adversarial-perturbation

Code and materials for the paper "Regional Image Perturbation Reduces Lp Norms of Adversarial Examples While Maintaining Model-to-model Transferability" (ICML 2020, UDL).

mutate-and-observe

Materials for the paper (Bioinformatics) "Mutate and Observe: Utilizing Deep Neural Networks to Investigate the Impact of Mutations on Translation Initiation"

cnn-gifs