Optimal Deep Learning Model for Olive Disease Diagnosis Based on an Adaptive Genetic Algorithm

Table 1

Machine learning and deep learning models for plant disease detection.

Fruit	Application	Technique	Ref
Machine learning-based models
Mixed	Classification	Threshold-based pixel level image subtraction	[30]
Apple	Detection	Graph-based k-means FCM clustering	[31]
Tomato	Quality assessment	Otsu method	[32]
Papaya	Disease detection	K-means clustering, SVM, decision tree, and Naive Bayes	[33]
Olive	Classification	Histogram of gradients of R, G, and B channel and FDA	[34]
Tomato	Classification	HSI-based color matching and BPNN	[35]
Orange	Classification	Naive Bayes, ANN, and decision tree	[36]
Deep learning-based models
Tomato	Disease detection	VGG-16 and ResNet	[37]
Apple	Disease detection	AlexNet	[38]
Banana	Disease detection	ResNet50, InceptionV2, and MobileNetV1	[39]
Plant Village	Disease detection	ResNet, VGG, and DenseNet	[40]
Plant Village	Disease detection	AlexNet, VGG16, and ResNet	[41]
Tomato	Disease detection	DNN	[42]