DeepLeaf-AI-Powered Plant Disease Detection and Diagnosis Using CNN and VGG-19

The paper developed a disease detection model for plant leaf diseases based on image processing and deep learning techniques that help detect diseases in the early stages of their development. Preprocessing techniques like resizing, converting to grayscale, segmentation, and features extraction can help enhance the quality of input images, making disease prediction easy. The paper employs techniques like CNN and VGG-19 for the purposes of predicting and classifying diseases in the leaves of plants. The proposed technique is aimed at detecting whether the plant leaves suffer from any disease, finding out some of the causes of the particular disease detected, and providing suggestions on how to prevent the problem. The addition of a GUI created in Python Tkinter allows easier access to prediction and uploading plant leaf pictures. Thus, this method will minimize manual diagnosis and ensure early detection of diseases among crops.

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