Table 9.
The impact of features descriptors on the performance of AOA against other recent optimizers over F-score measures
| F-score | GT dataset | FEI dataset | ||||
|---|---|---|---|---|---|---|
| Algorithms | HOG | LBP | GLCM | HOG | LBP | GLCM |
| HHO | 0.8977 | 0.8427 | 0.8953 | 0.9887 | 0.9379 | 0.9924 |
| SCA | 0.8892 | 0.8428 | 0.8866 | 0.9862 | 0.9549 | 0.9888 |
| EO | 0.9026 | 0.8400 | 0.8922 | 0.9925 | 0.9547 | 0.9900 |
| EPO | 0.8981 | 0.8496 | 0.8898 | 0.9875 | 0.9388 | 0.9848 |
| MRFO | 0.9058 | 0.8328 | 0.8896 | 0.9950 | 0.9499 | 0.9925 |
| HGSO | 0.8918 | 0.8359 | 0.8854 | 0.9925 | 0.9397 | 0.9938 |
| MVO | 0.9004 | 0.8351 | 0.8967 | 0.9925 | 0.9449 | 0.9925 |
| AOA | 0.9050 | 0.8422 | 0.9009 | 0.9950 | 0.9453 | 0.9950 |