Adversarial-Machine-Learning-Clinic/wiki/Timeline.md

= Timeline of Progress =

== Tuesday, February 27th, 2024 ==

• Determined that lack of effectiveness for low values of epsilon for the FGSM attack is normal (PyTorch Example Results).
• Finished trainable, saveable MNIST model
• Working on manipulating the MNIST dataset for cross validation and filtering
• Looking into implementing CIFAR-10 due to the model architecture and the nature of the images being classified

== Thursday, February 29th, 2024 ==

• Created functionality for Kuwahara filtering of batches of 64 images at runtime
• Encountering crash in last batch

== Monday, March 4th, 2024 ==

• Last batch of epoch doesn't have 64 images, batch size now variable
• Encountered crash when testing at end of epoch
  • Fixed crash, testing required specifying batch size
• All 14 epochs train successfully on filtered data
• Added --filter option to enable filtering on training and test data
  • Encountered crash, args not passed to test function
  • args variable now passed to test function
  • Filtered and unfiltered models saved to different files
• Tested filtered model with FGSM attack
  • Got results inline with unfiltered model
  • Realized that I forgot to save the filtered model
  • Tested actually filtered model with FGSM attack
  • Got really good results inline with hypothesis