Table 4 Accuracy of two imaging techniques with different models for testing disease Classification
From: A deep learning model for rapid classification of tea coal disease
Image type | Model | Accuracy (%) |
|---|---|---|
RGB image | ResNet18 | 60 |
VGGNet16 | 58 | |
AlexNet | 52 | |
WT-ResNet18 | 70 | |
WT-VGGNet16 | 64 | |
WT-AlexNet | 57 | |
Hyperspectral image | UVE-LSTM | 80 |
CARS-LSTM | 95 | |
NONE-LSTM | 90 | |
UVE-SVM | 61 | |
CARS-SVM | 77 | |
NONE-SVM | 65 |