Published Paper Details:

This research paper introduces a novel application for predicting plant diseases and curing the disease by using Convolutional Neural Networks (CNNs). Separate CNN models were trained on labeled datasets like cotton and potato leaves, each associated with their respective diseases. The primary goal is to employ of two standard CNN systems to detect various diseases in cotton and potato plants. Given India's heavy reliance on agriculture, this innovation is crucial to address challenges faced by the sector, including technological limitations, limited access to credit and markets, and the impact of climate change. this research paper are susceptible to various diseases that can impede their growth and result in substantial yield losses. The conventional disease detection methods involve manual inspection and disease prognosis, which are time consuming and less accurate. The research show- cases the effectiveness of the automated plant disease detection and curing system, with two best models achieving impressive accuracies of 97.10% and 96.94% . These results offer promising insights for potential applications in crop management, benefiting the agricultural sector and contributing to increased productivity and profitability.