Tomato Leaf Disease Classification

• Tech Stack: Python, google colab notebook, MATLAB, Tensorflow, Keras 3 API, Swarm Intelligence
• Research Paper: Link
• Github URL: Project Link

Presented a paradigm for automated computer-aided identification and diagnosis of interpretable tomato leaf diseases.

Eliminates the need for manual feature extraction by using Deep Learning techniques for non-hand-crafted feature utilization.

Utilizing our suggested Modified MobileNetV-3 architecture with hyper parameter optimization, our method incorporates features from the pre-trained model to enable a thorough feature representation that successfully addresses the over-fitting issue and improves the classification score of tomato leaf disease identification.

Utilizing state-of-the-art explainable AI techniques to propose a new paradigm in the Interpretability of deep learning models.