A CNN-BiLSTM Hybrid for Plant Leaf Disease Classification: Comparative Performance Evaluation of Deep Learning Algorithms
This study introduces a hybrid deep learning architecture that integrates squeeze-and-excitation residual blocks, capsule networks, bidirectional long short-term memory, and attention mechanisms, enabling farmers to obtain rapid, reliable, and cost-effective field diagnoses, thereby improving agricultural productivity...