Plant Disease Prediction

Plant Disease Prediction

Author Name : Prof. Manikrao M , Saima Danish

ABSTRACT Plant disease prediction is a crucial task in modern agriculture as it enables early detection and timely intervention, reducing crop loss and ensuring sustainable food production. This project aims to develop an accurate and efficient plant disease prediction system using techniques. allows leveraging pre-trained models on large-scale image datasets and adapting them to the specific task of plant disease classification. The proposed system utilizes a deep learning architecture, such as aconvolutional neural network (CNN), to learn discriminative features from plant images and classify them into healthy or diseased categories. The project involves collecting a diverse dataset of plant images with labeled disease conditions, preprocessing the data, fine-tuning a pre-trained CNN model, and training it on the dataset