Optimizing Convolutional Networks Using a Modified Metaheuristic for Apple Tree Leaf Disease Detection

The global demand for food is continuously increasing. The use of artificial intelligence can vastly improve the field of agriculture. Computer vision can help detect issues with crops. This work focuses on detecting plant diseases in apple tree leaves through the analysis of images. The proposed approach consists of a convolutional neural network (CNN) optimized by a hybrid optimization algorithm. The optimized models showcase favorable outcomes with the best models attaining an accuracy of 0.772408.