Adversarial-Machine-Learnin.../Filter_Analysis
2024-04-25 08:36:38 -04:00
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__pycache__ Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
data Loop over all filters and serialize results 2024-04-23 13:48:33 -04:00
images got data for fgsm mnist, working on displaying it 2024-04-24 12:16:09 -04:00
results Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
wiki Figure saving with proper size 2024-04-18 13:51:31 -04:00
cifar10_dla.pt Trained DLA on CIFAR-10 for 14 epochs. Achieved 82% accuracy 2024-04-25 08:36:38 -04:00
cifar10.py Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
DatasetImage.png Moved to separate project on Gitea 2024-02-22 13:39:09 -05:00
defense_filters.py Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
difference.png Moved to separate project on Gitea 2024-02-22 13:39:09 -05:00
display_results.py Converted old results to JSON format with metadata 2024-04-24 18:12:24 -04:00
dla.py Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
Filter_Performance_Against_FGSM_Attack_With_Snapped.png Implemented reduced color space (snapped color) filter 2024-04-05 17:18:25 -04:00
Filter_Performance_Against_FGSM_Attack.png Implemented reduced color space (snapped color) filter 2024-04-05 17:18:25 -04:00
kuwahara_FGSM_performance.png Tested models with filtered and unfiltered training data 2024-03-05 13:31:22 -05:00
mnist_cnn_bilateral.pt Models trained with various filters; kuwahara filter defense 2024-04-04 13:50:35 -04:00
mnist_cnn_filtered.pt Tested models with filtered and unfiltered training data 2024-03-05 13:31:22 -05:00
mnist_cnn_gaussian_blur.pt Models trained with various filters; kuwahara filter defense 2024-04-04 13:50:35 -04:00
mnist_cnn_unfiltered.pt Tested models with filtered and unfiltered training data 2024-03-05 13:31:22 -05:00
mnist.py Models trained with various filters; kuwahara filter defense 2024-04-04 13:50:35 -04:00
New_Snapped_Performace.png New implementation of color snapping 2024-04-06 22:31:31 -04:00
Plurality_Vote_Accuracy_Agaisnt_Individual_Filters_0.025_epsilon_step.png Decreased epsilon step size to 0.025 2024-04-10 12:23:55 -04:00
Plurality_Vote_Accuracy_Agaisnt_Individual_Filters.png 1-Bit, color snapping, and pluality vote accuracies 2024-04-07 12:04:46 -04:00
reformat_data.py Converted old results to JSON format with metadata 2024-04-24 18:12:24 -04:00
test_defenses.py Trained CIFAR-10 CNN, 60% accuracy, switching to DLA 2024-04-24 21:24:48 -04:00
unfiltered_FGSM_performance.png Tested models with filtered and unfiltered training data 2024-03-05 13:31:22 -05:00
whale_full.png Moved to separate project on Gitea 2024-02-22 13:39:09 -05:00
Whale-Attacked.png Moved to separate project on Gitea 2024-02-22 13:39:09 -05:00
Whale-Original.png Moved to separate project on Gitea 2024-02-22 13:39:09 -05:00