Table 2.
Measurements | Dataset 1 | Dataset 2 | Dataset 3 | ||
---|---|---|---|---|---|
Average-IOU (%) | 89.32 | 87.85 | 85.31 | ||
Maximum average-precision (AP) (%) | Nine classifiers | SVMSF | 91.47 | 89.82 | 80.72 |
SVMRBF | 90.41 | 90.45 | 90.05 | ||
SVMPF | 91.38 | 91.40 | 78.09 | ||
GNB | 89.22 | 90.88 | 84.44 | ||
MLP | 90.90 | 92.34 | 81.19 | ||
KNN | 89.87 | 84.48 | 75.87 | ||
RN | 94.90 | 91.22 | 86.47 | ||
DT | 68.63 | 59.81 | 46.43 | ||
EDT | 79.99 | 83.98 | 80.56 | ||
Maximum AP-ensemble learning (%) | 92.31 | 92.31 | 100.00 |