Leaf Disease Detection Using ResNet50

Abstract

Our primary target is to improve horticulture procedures which will be useful for farmers to gather the yield with no symptoms, infections. It improves the harvest amount and assists with developing normally by utilizing AI procedures. We had scanned for the monetary lopsided characteristics present in India. For a huge scope, we had discovered that horticulture is assuming a significant job, farmers are getting less yield, benefits because of occasional changes in climate making serious harm to the general public. These days AI is assuming a significant job in the field of man-made brainpower for n number of different applications. The total AI depends on preparing and assessment that is trying. Along these lines, we accepting leaf as the fundamental criteria to discover the ailments affecting and the principle point is to give preventive measures before happening of leaf diseases. Our proposed system is Resnet50 a profound layered system that has extremely enormous engineering utilized for the most part order reason for continuous applications. CNN assumes a significant job in picture handling. We had taken our own dataset of 1500 mango leaf pictures to identify Anthracnose ailment utilizing Resnet50 design.