Paper Contents
Abstract
The integration of deep learning technology has significantly advanced agricultural practices, particularly in the management of crop diseases. This study presents a web-based application designed to identify and classify plant diseases using image-based analysis. By utilizing pre-trained deep learning models, the application can recognize diseases across various crops such as cotton, corn, grape, potato, and tomato. This system enables real-time diagnostic feedback, supporting farmers and agricultural professionals with prompt and accurate disease recognition to enhance crop health and productivity. The paper describes the applied methodology, including data preparation, model training, and the creation of an accessible user interface. Results show that the system achieves a high accuracy rate in disease detection, underscoring the value of deep learning in contemporary agriculture.
Copyright
Copyright © 2024 Divya Mishra. This is an open access article distributed under the Creative Commons Attribution License.
