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January 1, 2026International Journal of Intelligent Information and Database SystemsOpen Access

A novel improved deep score recurrent convolutional neural network-based tomato plant disease identification framework

Sowmiya Murkesh Krishnaveni Sivamohan

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Key Points

To develop a new framework using deep learning for identifying diseases in tomato plants through image analysis.
Utilized a recurrent convolutional neural network architecture
Applied image processing techniques on tomato plant images
Evaluated the framework's accuracy and efficiency
Demonstrated improved accuracy in disease identification compared to previous methods
Reduced processing time for image classification
Enhanced recognition of multiple disease types in tomato plants

Implication

Novel deep learning framework identifies tomato plant diseases, suggesting enhanced agricultural practices.

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Cite This Study

Murkesh et al. (2026) studied this question.

synapsesocial.com/papers/69e473de010ef96374d8fa72 https://doi.org/10.1504/ijiids.2026.10077768

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