Classification of Maize leaf diseases from healthy leaves using Deep Forest
Jatin Arora, Utkarsh Agrawal, Prerna Sharma
Abstract
Apart from being relied upon for feeding the entire world, the agricultural sector is also responsible for a third of the global Gross-Domestic-Product (GDP). Additionally, a majority of developing nations depend on their agricultural produce as it provides employment opportunities for a significant fraction of the poor. This calls for methods to ensure the accurate and efficient diagnosis of plant disease, to minimize any adverse effects on the produce. This paper proposes the recognition and classification of maize plant leaf diseases by application of the Deep Forest algorithm. The Automated novel approach and accurate classification using the Deep Forest technique are a significant step-up from the existing manual classification and other techniques with less accuracy. The proposed approach has outperformed Deep Neural models and other traditional machine learning algorithms in terms of accuracy. It justifies its low dependency on extensive Hyper-parameter tuning and the size of the dataset as against other Deep Learning Models based on neural networks.