DEEP LEARNING BASED ORYZA SATIVA LEAF DISEASE DETECTION USING ALEX NET DEEP ARCHITECTURE

Abstract

Oryza Sativa is one of the essential food in Asia. Since there is a variety of rice and we use the rice in our daily life to get energy we should develop a method for the farmers to check the disease in the rice leaf so that they can find the solution in the beginning stage and the crop will not get destroyed by the disease. For quite half of the humanity rice shaped the economies of thousands of people. We should consider as an important part of each individual’s life and it is a staple food of almost half of the world’s population.  The research was proposed based on Deep Learning Technique to support rice plant disease classification method. A CNN is a Deep Learning algorithm used to absorb an image as an input and assign importance to the many objects in the image. The CNN method is support-ed by feature extraction and gives success to obtain results that classify the dis-ease successfully with 99% of accuracy.