Efficient Deep Learning Algorithm for Diagnosing the Flora Diseases

Abstract

The human race’s entire existence depends on agriculture. A relatively big portion of the people can find work in agriculture in addition to receiving food and raw materials. We are all aware that India’s economy depends heavily on agriculture, which is currently one of the world’s top two agricultural producers. 43 percent of the Indian workforce is employed there, and it produces around 16.5 percent of India’s GDP. This enables us to address the fact that India’s economy is expanding annually as a result of a rise in agricultural productivity. How effectively crops are free from numerous pests and diseases determine, in large part, how successful agriculture production and its economics are. The farmers are being severely impacted by the decrease in yield. Additionally, the nutritional value of the plant’s edible components is too diminished with decreased production. Making short-term modifications to daily agricultural activities that reduce losses brought on by unfavourable conditions and improve yield and quality of agricultural productions is substantially aided by early disease forecasts in the short and medium run. There are now many different misunderstandings regarding plant disease detection. Therefore, in this work, disease diagnosis using leaves is made simple and user-friendly. With this approach, we have suggested an automated method to identify the illness and offer a suitable treatment for it via an application.