Table 5 Comparison of different deep learning models.
From: An automated hybrid deep learning framework for paddy leaf disease identification and classification
DL Classifiers | Accuracy | Precision | Recall | F1-score |
|---|---|---|---|---|
CNN | 96.22 | 97.99 | 96.1 | 94.22 |
LSTM | 92.99 | 91.29 | 90.75 | 89.26 |
Bi-LSTM | 97.55 | 96.42 | 95.28 | 94.66 |
Bi-GRU | 90.81 | 92.54 | 91.88 | 92.11 |
CNN-LSTM | 91.25 | 91.85 | 90.15 | 91.92 |
CNN-Bi-LSTM | 95.18 | 94.48 | 93.21 | 92.12 |
CNN-GRU | 93.95 | 93.45 | 92.45 | 91.21 |
CNN-Bi-GRU | 94.25 | 94.81 | 93.73 | 90.75 |
MobileNetV3 + GKSO-SA | 98.52 | 95.45 | 96.96 | 97.54 |
