Leaf Disease Classification for Vegetable Farming using Artificial Intelligence
Abstract: This research paper explores the application of artificial intelligence (AI) techniques for the classification of leaf diseases in vegetable farming, utilizing Python as the primary programming language. The study aims to develop an accurate and efficient model to assist farmers in early detection and management of plant diseases, thereby improving crop yield and quality. By leveraging convolutional neural networks (CNNs), a dataset of diseased and healthy leaf images is processed to train and validate the AI model. The results demonstrate significant improvements in disease identification accuracy compared to traditional methods. The implementation of this AI - driven approach has the potential to revolutionize agricultural practices by providing a scalable, cost - effective solution for real - time disease monitoring and intervention.
Keywords: Artificial intelligence, Leaf diseases, Vegetable farming, Convolutional neural networks, Real - time monitoring
How to Cite?: Onyeachonam Dominic - Mario Chiadika, Ujerekre Ekoko, "Leaf Disease Classification for Vegetable Farming using Artificial Intelligence", Volume 13 Issue 6, June 2024, International Journal of Science and Research (IJSR), Pages: 269-273, https://www.ijsr.net/getabstract.php?paperid=SR24601192902, DOI: https://dx.doi.org/10.21275/SR24601192902