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Classification and identification of disease in potato leaf using hierarchical based deep learning convolutional neural network

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Abstract

Agriculture is a major source of income of a nation’s economy and it plays an important role in feeding mankind. Agriculturists and scientists are working hard to maximize productivity while minimizing the impact on the environment. One important aspect of smart agriculture is disease management in crops. Crops are affected by several diseases caused by pest infestation and pathogens like viruses, bacteria, and fungus. Diseases can be detected early which damage control is aided, and yield loss is avoided. In this paper, a Hierarchical Deep Learning Convolutional Neural Network (HDLCNN) is proposed to detect the diseases in the leaf. Initially, a pre-processing step is performed utilizing the Median Filtering method. This removes the noises in the image. After processing the image, an Intuitionistic Fuzzy Local Binary pattern (IFLBP) is introduced, it extracts the features of the leaf. Then the Hierarchical Deep Learning Convolutional Neural Network is used to detect and classify the disease and the Decision Support Systems help farmers implement effective treatment programs. These allow farmers to increase the efficiency of control techniques without increasing the risks. This method is evaluated and executed in the Matlab Simulink software. While compared to different methods, the proposed technique performs better performance, existing methods are VGG-INCEP, Deep CNN, Random forest methods (RF) and other Spiking neural networks (SNN) models. The accuracy, precision, recall, and F-score of the proposed method is approximately 4%, 6%, 3%, and 3.5% higher than the other existing methods. Then the specificity, sensitivity, and PSNR of the proposed method is 4.5%, 1%, and 2% higher than the existing methods. Thus utilizing this proposed HDLCNN, its performance of the method is improved and this research alerts the former. Through this the former can prevent the leaf from diseases, thus the crop of potato is improved worldwide.

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  1. Bakhtiyarpur College of Engineering, Champapur, Deduar, Bakhtiyarpur(Bihar), India

    Alok Kumar & Vijesh Kumar Patel

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  1. Alok Kumar
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  2. Vijesh Kumar Patel
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Correspondence to Alok Kumar.

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Kumar, A., Patel, V.K. Classification and identification of disease in potato leaf using hierarchical based deep learning convolutional neural network. Multimed Tools Appl 82, 31101–31127 (2023). https://doi.org/10.1007/s11042-023-14663-z

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  • DOI: https://doi.org/10.1007/s11042-023-14663-z

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