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January 1, 2025International Journal of Signal and Imaging Systems EngineeringOpen Access

Robust Cotton Leaf Disease Classification Using Hybrid Deep Learning Approach with Multi- Loss Function

Sailaja Madhu V. Ravi Sankar

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Key Points

Hybrid deep learning models enhance classification accuracy of cotton leaf diseases significantly.
The multi-loss function approach improved model performance, achieving up to 92% accuracy in tests.
Analysis incorporates various datasets of cotton leaf images to develop a solid classification framework.
Improved methods for disease classification in plants may support better crop management policies.

Implication

Observational analysis finds enhanced classification accuracy for cotton leaf diseases, suggesting improved agricultural outcomes.

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Cite This Study

Madhu et al. (2025) studied this question.

synapsesocial.com/papers/69a75aa4c6e9836116a20bb2 https://doi.org/10.1504/ijsise.2025.10075940

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