A ConvNeXt–Liquid Neural Network framework for accurate RL disease classification

2026-08-08

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ShivaPrasad Namala

Sridhar Chintala *

Damodar Reddy Edla

DOI：10.1016/j.compag.2026.112271

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• A hybrid ConvNeXt–LNN framework is proposed for rice leaf disease classification. • LNNs enable adaptive feature refinement and stabilization for static image analysis. • The framework improves robustness under illumination, noise, and occlusion variations. • Comprehensive validation includes ablation, robustness, and statistical analyses. • High classification performance is achieved with low computational complexity.

Keywords:

Artificial intelligence

Deep learning

Plant disease diagnosis

Agricultural imaging

ConvNeXt

Liquid Neural Networks

Rice disease detection

A ConvNeXt–Liquid Neural Network framework for accurate RL disease classification

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