An Overview on Plant Disease Detection Algorithm Using Deep Learning

Abstract

Disease detection in plants is one of the major concerns for farmers nowadays. As many new techniques like Deep Learning capability to dive into deep analysis and computation made it one of the prominent techniques for plant leaf disease detection. Mobile applications with inbuilt deep learning models are helping farmers to detect and classify the disease throughout the world. It consists of disparate techniques like ANN and CNN to diagnose the disease in plant leaves. It uses key features of images to detect and diagnose the type of diseases present in leaves. Some pre-trained models like AlexNet, GoogleNet, LeNet, ResNet, VGGNET and Inception with a huge number of learnable parameters had shown classification or detection of disease in leaves. This paper focused on different architecture like predefined and user defined models that were used for detection of diseases in plant leaves.