Enhancing Rice Leaf Disease Classification: A CNN-SVM Approach

Banerjee, Deepak; Kukreja, Vinay; Srivastava, Prateek; Bhattacherjee, Abhishek; Joshi, Kireet

doi:10.1109/esci59607.2024.10497326

2024 International Conference on Emerging Smart Computing and Informatics (ESCI) 2024

DOI: 10.1109/esci59607.2024.10497326

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Enhancing Rice Leaf Disease Classification: A CNN-SVM Approach

Deepak Banerjee,

Vinay Kukreja,

Prateek Srivastava

et al.

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Utilizing Convolutional Neural Networks for the Effective Classification of Rice Leaf Diseases Through a Deep Learning Approach

Akter,

Sumon,

Ali

et al. 2024

Electronics

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Rice is the primary staple food in many Asian countries, and ensuring the quality of rice crops is vital for food security. Effective crop management depends on the early and precise detection of common rice diseases such as bacterial blight, blast, brown spot, and tungro. This work presents a convolutional neural network model for classifying rice leaf disease. Four distinct diseases, bacterial blight, blast, brown spot, and tungro, are the main targets of the model. Previously, leaf pathologies in crops were mostly identified manually using specialized equipment, which was time-consuming and inefficient. This study offers a remedy for accurately diagnosing and classifying rice leaf diseases through deep learning techniques. Using this dataset, the proposed CNN model was trained to identify complex patterns and attributes linked to each disease using its deep learning capabilities. This CNN model achieved an exceptional accuracy of 99.99%, surpassing the benchmarks set by existing state-of-the-art models. The proposed model can be a useful diagnostic and early warning system for rice leaf diseases. It could help farmers and other agricultural professionals reduce crop losses and enhance the quality of their yields.

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Utilizing Convolutional Neural Networks for the Effective Classification of Rice Leaf Diseases Through a Deep Learning Approach

Akter,

Sumon,

Ali

et al. 2024

Electronics

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Enhancing Rice Leaf Disease Classification: A CNN-SVM Approach

Cited by 1 publication

References 14 publications

Utilizing Convolutional Neural Networks for the Effective Classification of Rice Leaf Diseases Through a Deep Learning Approach

Utilizing Convolutional Neural Networks for the Effective Classification of Rice Leaf Diseases Through a Deep Learning Approach

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