Table 1.

Summarization of the existing work.

Paper references	DL model	Dataset	Class	Accuracy (%)
Mohanty et al.14	AlexNet, GoogleNet	PlantVillage14	38	99.34
Ferentinos et al.15	AlexNet, VGG, Overfeat, GoogleNet AlexNetOWTBn	PlantVillage14	58	99.48
Geetharamani et al.32	Nine layer CNN	PlantVillage14	38	96.46
Chen et al.33	VGGNet with two inception layer	Maize dataset14	4	84.25
Sethy et al.34	11 state-of-art CNN architecture with SVM for classification	Rice dataset34	4	98.38
Too et al.18	Fine tune 6 different CNN models	PlantVillage14	38	99.76
Atila et al.19	EfficientNet	PlantVillage14	38	99.38
Zeng et al.21	Self-attention CNN with Residual Connection	AES-CD9214 MK-D2 dataset35	6	95.59
Qian et al.23	Transformer and Multi- head attention	Maize dataset14	4	98.7
Pandey24	DADCNN-5	PlantVillage14	38	99.93
Bhujel et al.25	CNN with Multiple attention	Tomato leaf14	10	99.69
Lu et al.27	GET	GLDP12k dataset27	11	98.14
Yu et al.28	ViT architecture	Ibean36	3	99.22
Borhani et al.29	ViT architecture	Wheat rust37	3	100
Mohamed Zarboubi et al.26	CustomBottleneck- VGGNet	PlantVillage14	10	99.12
Abdelaaziz Bellout et al.31	LT-YOLOv10n	Roboflow Universe, PlantVillage14	9	98.7
Bellout et al.30	Multiple YOLO architecture	PlantVillage14 PlantDoc38	3	93.1