Convolutional Neural Network deep learning model for early detection of streak virus and lethal necrosis in maize: A case of Northern-highlands, Tanzania.

The goal of this study is to develop a deep learning model to predict the early occurrence of Streak Virus and Lethal Necrosis in maize leaves and then deploy the model in a mobile app. We developed a convolutional neural network model from scratch and trained it using 1500 images dataset belonging to three classes namely; HEALTHY, MLN and MSV which attained a validation accuracy of 98.44%. However, we plan to develop pre-trained models to compare the results with those already attained and select the best model to be deployed in a mobile app for early detection and testing in real life environment.