Research Article
Enhancing Structural Crack Detection through a Multiscale Multilevel Mask Deep Convolutional Neural Network and Line Similarity Index
Table 6
Comparison of estimation accuracy for crack-detection methods.
| Image-set | DNN methods | Metric (%) | FPS | ODS | OIS | AP |
| Indoor test set (total 10 images) | MSML mask DCNN w/four scale layers | 20.12 | 21.53 | 5.39 | 6.98 | MSML mask DCNN w/four scale layers w/LSI | 29.86 | 29.99 | 12.35 | 5.10 | Surf & CNN-based classification model [13] | 8.55 | 6.43 | 1.98 | 21.58 | Mask R-CNN [14] | 9.58 | 8.59 | 2.12 | 23.63 | Dual-scale CNN-based classification [15] (GoogLeNet & ResNet) | 15.73 | 11.28 | 4.32 | 10.23 | CrackPix [16] | 13.30 | 10.19 | 2.40 | 15.33 |
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(Best scores shown in bold font).
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