A Hybrid Deep Learning Model with Bayesian Optimization Technique for Leaf Disease Classification
Detecting plant diseases on time is imperative to improve agricultural productivity and mitigate economic losses. This study presents a novel artificial intelligence framework for classifying plant diseases, combining advanced deep learning technologies with a hyperparameter optimization strategy. Specifically, we employed a hybrid architecture that concatenates two pre-trained models, MobileNetV2 and DenseNet201, enriched with custom layers developed by the researchers. Bayesian Optimization was employed to enhance model performance, focusing on four critical hyperp