Table 5 Performance assessenment of anticipated method with contemporary methods.
From: A lightweight deep learning method for medicinal leaf image classification using feature fusion
DL Models | 224*224 | 256*256 | 128*128 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
Accuracy | Precision | Sensi tivity | Speci ficity | Accuracy | Precision | Sensi tivity | Speci ficity | Accuracy | Precision | Sensi tivity | Speci ficity | |
RestNet | 97.21 | 97.01 | 97.12 | 97.02 | 96.17 | 95.71 | 96.025 | 96.078 | 95.07 | 95.013 | 95.012 | 95.014 |
Inception | 96.21 | 96.19 | 96.12 | 96.02 | 95.102 | 95.124 | 95.128 | 95.124 | 94.02 | 94.017 | 94.016 | 94.012 |
Xception | 94.23 | 94.21 | 94.231 | 94.125 | 93.24 | 93.254 | 93.264 | 93.264 | 92.12 | 92.014 | 92.014 | 92.014 |
VGG | 96.21 | 97.213 | 97.213 | 97.223 | 96.021 | 96.024 | 96.024 | 96.021 | 95 | 95.012 | 95.012 | 95.012 |
MobileNet | 92.1 | 92.1 | 92.1 | 92.12 | 92.12 | 92.1 | 92.1 | 92.1 | 90.12 | 90.013 | 90.013 | 90.013 |
GoogleNet | 95.22 | 95.23 | 95.24 | 95.25 | 95.24 | 95.254 | 95.264 | 95.264 | 94.24 | 94.213 | 94.213 | 94.213 |
FN-NCA-CNN | 98.9 | 98.854 | 98.856 | 98.84 | 97.9 | 97.854 | 97.836 | 97.834 | 98.0834 | 98.082 | 98.0856 | 98.084 |
