Abstract
AgroDetect Smart Plant Pathology is a Web-App-based solution and an
innovative system that utilizes image processing techniques to analyze
plant diseases based on leaf images. This technology aims to
revolutionize agriculture by offering a rapid and precise method of
identifying and managing plant diseases, ultimately improving crop yield
and reducing losses. The Convolutional Neural Network (CNN) model,
augmented with Rectified Linear Unit (ReLU) activation functions, was
employed to discern the condition of plants by analyzing leaf images.
The accuracy of the performance of the designed models is evaluated
using four categories of plant leaves from the PlantVillage database.
The average accuracy of the designed models is around 97% and is
further compared with state-of-art works and also designed a web
application using the Streamlit Python library for user interaction with
minimal effort.