Deep Learning Mobile App Based Microscopic Leaf Imaging Disease Classification with Azure Cloud Computing Service

The growth of rubber trees always suffer from blight disease that can be detected on the leaves. Several studies show that an early detection of blight disease may contribute to a positive turnout recovery rate. In this paper, a mobile app-based microscopic leaf imaging disease classification is proposed to detect infected leaves that provides a probability of disease types, geo-tagging location, and smart reporting with recovery stage to assist productivity workflow. Super Resolution Generative Adversarial Network is applied to upscale a low resolution microscopic leaf imaging while introducing finer texture detail. After super resolution reconstruction, a convolution neural network classifier is performed to classify disease groups with an improved accuracy. The diagnostic solution is designed on the Azure cloud computing service to manage the plant disease database, perform reinforcement learning, host web application, secure authentication and display valuable insight of recovery.