Table 4 Classification results of different classifiers and different texture features
From: Cotton stubble detection based on wavelet decomposition and texture features
Features | Model | Â | Accuracy (%) | Sensitivity (%) | Specificity (%) | Time (per/ms) |
|---|---|---|---|---|---|---|
GLCM | RF | Â | 89 | 87.5 | 97.3 | 43.5 |
| Â | BPNN | Â | 89.4 | 93.8 | 96.6 | 43.4 |
| Â | SVM | Linear | 88.1 | 90.6 | 95.9 | 44.1 |
| Â | Â | Polynomial | 87.1 | 90.6 | 95.2 | 44.5 |
| Â | Â | RadialBasis | 88.1 | 89.1 | 95.9 | 45.1 |
| Â | Â | Sigmoid | 81.4 | 82.8 | 95.9 | 45.1 |
GLRLM | RF | Â | 60.5 | 32.8 | 89 | 1080.1 |
| Â | BPNN | Â | 67.6 | 37.5 | 93.2 | 1080.6 |
| Â | SVM | Linear | 64.3 | 35.9 | 89.7 | 1084.2 |
| Â | Â | Polynomial | 54.3 | 28.1 | 84.2 | 1085 |
| Â | Â | RadialBasis | 60.5 | 28.1 | 86.3 | 1086.5 |
| Â | Â | Sigmoid | 48.6 | 18.8 | 87 | 1086.3 |
LBP | RF | Â | 46.1 | 23.4 | 87 | 1391 |
| Â | BPNN | Â | 46.7 | 24.6 | 79.9 | 1386 |
| Â | SVM | Linear | 44.8 | 18 | 82 | 1397 |
| Â | Â | Polynomial | 45.2 | 17.3 | 85.1 | 1397.7 |
| Â | Â | RadialBasis | 46.9 | 14.8 | 89.5 | 1398.8 |
| Â | Â | Sigmoid | 44.2 | 21.7 | 78.1 | 1398.8 |