Research Article
Automated Pavement Crack Damage Detection Using Deep Multiscale Convolutional Features
Table 3
Comparisons of the proposed and other methods on the CrackDataset.
| Method | OA | Precision | Recall | -score | mIoU |
| CrackForest [15] | 87.04 | 86.28 | 85.46 | 85.86 | 59.26 | SegNet [37] | 96.64 | 96.86 | 97.08 | 96.97 | 70.56 | U-Net [21] | 96.58 | 96.99 | 97.09 | 97.04 | 71.49 | PSPNet [38] | 96.25 | 96.90 | 96.88 | 96.89 | 69.63 | DeepLabv3+ [39] | 96.83 | 97.01 | 97.64 | 97.32 | 71.77 | DeepCrack [30] | 97.14 | 97.33 | 97.72 | 97.52 | 72.04 | CrackSeg | 98.79 | 98.00 | 97.85 | 97.92 | 73.53 |
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