This is my final thesis project focused on recognizing diseases in coffee berry diseases using deep learning models. The study emphasizes transfer learning on a Rwandan Arabica coffee dataset with four disease classes:

Coffee berry borer coffee berry disease Leaf rust Healthy Leaves The DenseNet model was identified as the most accurate, achieving a classification accuracy of 56.57%.