Plant Disease Detection Using Deep Learning Model - Application FarmEasy
Pallavi Pandey, Kalpesh Patyane, Manish Padekar, Rohan Mohite, Panjab Mane, Anil Avhad
Abstract
“FarmEasy” will be a single platform for all activities related to farming and crop diagnostics. The platform’s ability to detect and recognize pests is its most crucial component. In the realm of computer automation, to detect disease through plant leaves is a vital study theme. This is a technique that gathers plant photos using computer vision technologies and utilizes those images to determine whether any disease is present. This system aims to detect plant diseases by analyzing images of plant leaves. It utilizes machine learning and computer vision algorithms to identify the presence of various diseases such as powdery mildew, leaf rust, and blight. The system can provide accurate and quick results, enabling farmers to take immediate action to prevent the spread of the disease and minimize crop losses. This technology can help to enhance the efficiency and sustainability of agriculture by reducing the need for manual inspection and enabling early disease detection. The importance of early disease detection in plants, which can help prevent the spread of disease and increase crop yields.