Precision in Plant Disease Diagnosis: A CNN Approach to Enhance Agricultural Practices
Our project is dedicated to addressing this critical need by harnessing the power of Convolutional Neural Networks (CNNs). These neural networks are adept at learning intricate patterns and features from images, equipping them with the capability to distinguish between healthy and infected plants with remarkable precision
Methodology Overview
To accomplish our goal, we will undertake a comprehensive evaluation of two CNN models: one built from scratch and another utilizing pre-trained weights. Through a thorough analysis of various metrics, we aim to determine which model exhibits superior accuracy in plant disease detection, thereby contributing to the advancement of agricultural practices.
Dataset
The dataset has been generated by applying offline augmentation techniques to the original dataset, which is accessible on this GitHub repository: https://github.com/spMohanty/PlantVillage-Dataset.