A Sqeeze Net Based Paddy Disease Classification

The most widely grown crop in the nation is paddy. The lack of nutrients and pathogens causes a significant amount of crop loss. The management of diseases is the answer to minimizing this loss. Human experts mostly do disease management. Agriculture domains rely on image-based methods with artificially intelligent systems for effective disease management solutions. This paper presents the implementation of a Squeeze Net pre-trained network, which is derived from deep neural networks. The network was applied to a preprocessed data set including several paddy diseases. The experimental results indicate that Squeeze-Net achieved an exceptional classification accuracy of 97.26%.