Tags:Convolutional neural networks, Crop diseases, Date palm tree diseases detection, Deep learning, Leave classification, Leaves discoloration detection and Transfer learning
Abstract:
Most countries are concerned about the quality of their agricultural products. All facilities involved in the agricultural food production cycle must be examined. So, there are many challenging are facing this field, and the most prominent of these are crops diseases. In order to keep UAE one of the leading countries in producing dates, a date palm leaves discoloration detection system based on deep learning is proposed. This system uses three different convolutional neural networks (CNN) models, which are SqueezeNet, GoogleNet, and AlexNet. All of the three models show a high validation & testing accuracy with a convenient training time. SequeezeNet achieved the best test accuracy, which is 98%. The proposed system helps dates producers and farm owners to reduce the risk of diseases, and in turn, production and workforce expenses specially in remote areas and large farms.
Date Palm Leaves Discoloration Detection System Using Deep Transfer Learning