| Autor: |
Joshi, Jahanvi, Vats, Siddhant, Sharma, Shilpi, Sahu, Geet, Debnath, Narayan C. |
| Předmět: |
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| Zdroj: |
International Journal for Computers & Their Applications; Sep2024, Vol. 31 Issue 3, p214-220, 7p |
| Abstrakt: |
Plants serve as a great source of energy, yet their potential ability is affected due to biotic and abiotic disease, in turn affecting crop yield. Though significant research has been made in this field, early disease detection and prevention across multiple plant species still serve as a major challenge in the agricultural industry. This paper proposes a framework involving the detection of diseases in leaves with the Convolutional Neural Network (CNN) approach and utilizing computer vision and deep learning models. The proposed new model presents a comprehensive in-depth solution for advanced agricultural practices. The research also offers a shift towards efficient, accurate, and sustainable management of challenges associated with agriculture, specifically species recognition, disease assessment, and remediation strategies. Comparison of the proposed model with some other available models in the literature is included. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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