Table 5.
The impact of features descriptors on the performance of AOA against other recent optimizers over Accuracy measures
| Accuracy | GT dataset | FEI dataset | ||||
|---|---|---|---|---|---|---|
| Algorithms | HOG | LBP | GLCM | HOG | LBP | GLCM |
| HHO | 0.8990 | 0.8689 | 0.8960 | 0.9831 | 0.9320 | 0.9887 |
| SCA | 0.8914 | 0.8660 | 0.8887 | 0.9841 | 0.9534 | 0.9864 |
| EO | 0.9031 | 0.8651 | 0.8953 | 0.9889 | 0.9506 | 0.9864 |
| EPO | 0.8993 | 0.8669 | 0.8917 | 0.9840 | 0.9370 | 0.9815 |
| MRFO | 0.9028 | 0.8636 | 0.8944 | 0.9893 | 0.9456 | 0.9889 |
| HGSO | 0.8944 | 0.8578 | 0.8873 | 0.9881 | 0.9349 | 0.9886 |
| MVO | 0.9020 | 0.8624 | 0.8997 | 0.9865 | 0.9392 | 0.9875 |
| AOA | 0.9034 | 0.8701 | 0.9014 | 0.9916 | 0.9561 | 0.9904 |