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The framework integrates an optimized feature fusion algorithm using pre-trained CNN models to improve disease detection accuracy. Rice leaf images are processed to classify plants as either healthy or diseased with greater accuracy compared to conventional methods. Experiments conducted on publicly available datasets demonstrate that the proposed Twin CNN architecture, combined with a robust feature fusion mechanism, outperforms existing methods in terms of accuracy and computational efficiency. 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