Texture and Colour based Plant Leaf Disease detection using DenseNet
In the agricultural sector, production in terms of quality and quantity relies on the healthy condition of plant leaf which means the production is affected by the diseases of a plant leaf. A fast reliable non-destructive method uses to detect the issues in the process of diagnosis of plant leaf diseases in early stages which is beneficial for farmers to achieve a higher quality of production. In this paper, Plant Village dataset utilizes to get the images of leaf leaves to include diseases and a healthy class and it is also used as an input source to derive the architectures of deep learning neural networks such as AlexNet, ResNet, and DenseNet. The analysis of accuracy and execution time in classification has been considered based on the number of images and hyper-parameters like weight, mini-batch size, and bias learning rate.