Potato-Y virus detection using XAI

As part of the Professorship of Applied Sciences in Computer Vision and Data Science

Goal	Detect the potato-Y virus infection using AI.
Main challenge	The limited availably of image data of diseased potato plants combined with the subtle visual distinction of diseased and non-diseased plants.
Result	An AI model that detects the potato-Y virus from images and an explainable AI output that shows which input-pixels caused the decision.
Future	Integration of advanced XAI to improve debugging of models that are prone to overfitting due to small datasets.