Comparative Study using Deep Learning for Detecting Plant Type and Leaf Disease

Plant diseases are growing significantly in the recent years due to severe climatic changes and a lack of immunity in the plants. Large-scale crop destruction results from this, which reduces the cultivation and ultimately affects the farmers money. Identification and treatment of the disease have become quite difficult due to the rapid development in the number of diseases and the inadequate understanding by human. On the other hand, various studies say that the texture and visual resemblance of the leaves are characteristics that help for the disease type identification. Hence the solution to this challenge can therefore be found by combining deep learning and computer vision. We proposed a model based on deep learning in the present work. It is trained on public datasets that contain pictures of both healthy and damaged plant leaves. The model accomplishes this goal by categorizing photos of sick leaves