ABSTRACT
Artificial intelligence and machine learning are domain of computer science which have changed the vision of the world completely over the past few years. Deep learning models are extensively being used in precision farming and smart agriculture. In this chapter, different maize leaf diseases such as grey leaf spot, common rust and northern leaf blight are analyzed using the deep learning techniques. In this work, two convolutional neural network (CNN) models, namely custom-designed CNN and a pre-trained neural network called AlexNet with transfer learning, are used for classification of maize leaf diseases. Classification results are critically evaluated using different multiclass classification metrics. The results are competent with the existing methods in this domain. Our proposed material and models are able to give promising classification accuracy results of up to 97.81%.
