


Volume 20 No 20 (2022)
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Classification of Diseases in Rice Crops using Deep Convolutional Neural Networks for Agricultural Applications
Rajesh Kanna.R , Dr.V.Ulagamuthalvi ,Umadevi.G
Abstract
Agricultural crops are the important sources of energy, and are the primary way to resolve the crisis of global
warming. There are various diseases that affect the agricultural crop health with the potential to source disturbing
social, economical, and ecological losses. Over number of agricultural crops, rice acts as the major grain all over the
world, and hence it is important to identify the type of the disease that attack the rice crop at early as possible in such
a way to choose the proper pesticide to be used. This paper proposes a deep convolutional neural network (Deep
CNN) based disease classification strategy for rice crop with the aid of the significant features of the input image.
The proposed strategy possesses enhanced convergence characteristics and capable to deal with dataset of larger
size. The effectiveness of the proposed model is deliberated by comparing the performance with the existing
methods, in terms of the performance metrics, such as accuracy, precision, and recall. The accuracy, precision, and
recall of the proposed method are attained to be 95.9181%, 94.2515%, and 97.125%, respectively, which shows the
superiority of the proposed method in classification of diseases in rice plant.
Keywords
Agriculture, rice crop disease classification, crop health, pesticide, deep Convolutional neural network.
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