Plant Disease Prediction Using Machine Learning

Plant Disease Prediction Using Machine Learning

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Abstract:

Plant disease prediction is crucial for agriculture as it helps in reducing crop damage and improving yields. This project proposes a machine learning-based approach for plant disease prediction using image analysis. A deep learning model is trained on a dataset of images of healthy and diseased plants to learn features and patterns. The model is then used to classify new images as healthy or diseased. The proposed approach achieves high accuracy and can be used by farmers and agricultural experts to identify diseases at an early stage, enabling timely treatment and reducing crop loss. This project demonstrates the potential of machine learning in plant disease prediction and its application in precision agriculture.

Keywords:

Plant Disease Prediction, Machine Learning, Image Analysis, Deep Learning, Precision Agriculture, Crop Yield Management, Agricultural Technology, Disease Detection, Image Classification

Project include:

1. Synopsis

2. PPT

3. Research Paper

4. Code

5. Explanation video

6. Documents

7. Report

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