Time saving malady expert system in plant leaf using cnn

Abstract

Diseases in plants are quite natural but the Protection of plants in whole cultivation is a difficult process. It needs  a clear knowledge of the plants behavior of growth and their likely affected  bacteria and microorganisms.Commonly the botanists observe the leaf with naked eye for the classification of diseases. But this method can be time consuming, expensive and less accurate and it affects the agricultural production of the country . This system deals with an advanced deep learning neural network  approach to the development of plant malady recognition expert systems based on the external changes occurring in the leaves. This system works by capturing the images of leaves by using a camera or uploading an image so that it classifies the infected diseases. Innovative type of learning  methods facilitate a rapid and simple classification execution put into practice. The methodology proposed in this system is a innovative move toward in detect diseases  in plants using deep learning trained and fine-tuned to fit precisely to the file of a plant’s leaves .The  Innovation of the developed model includes its easiness; disinfected  leaves and environment images are in procession with other classes, allow the model to distinguish between infected leaves and normal ones  from the data and also recommend the pesticides for the infected diseases.