Research on Intelligent Recognition Method of Tobacco Leaf Maturity Based on Deep Learning
This study proposes a robust, real-time deep learning framework that integrates a ViT-CBAM architecture with MSRCR illumination normalization and multi-space color feature engineering to achieve high-accuracy, automated recognition of tobacco leaf maturity for precision agriculture.