AI-Based Crop Disease Detector is a deep learning solution that leverages Convolutional Neural Networks (CNNs) to automatically identify and classify crop diseases from leaf images. The dataset was cleaned, preprocessed, and augmented to improve robustness and accuracy. Multiple experiments were conducted to optimize model performance and minimize false predictions. The final model was integrated into a user-friendly web application enabling real-time disease diagnosis.
This innovation empowers farmers to detect issues early, improve yield, and reduce agricultural losses. Tools used include Python, Pandas, NumPy, SQL, Jupyter Notebook, and Git.
