Research Article
Enhancing Structural Crack Detection through a Multiscale Multilevel Mask Deep Convolutional Neural Network and Line Similarity Index
Table 8
Comparison of estimation accuracy for crack-detection methods.
| Image-set | DNN methods | Metric (%) | FPS | ODS | OIS | AP |
| Underground tunnel test set (total 20 images) | MSML mask DCNN w/four scale layers | 34.22 | 35.41 | 11.88 | 7.05 | MSML mask DCNN w/four scale layers w/LSI | 44.31 | 42.94 | 20.21 | 5.98 | Surf & CNN-based classification model [13] | 9.12 | 7.18 | 4.59 | 19.65 | Mask R-CNN [14] | 10.91 | 9.69 | 7.53 | 23.91 | Dual-scale CNN-based classification [15] (GoogLeNet & ResNet) | 22.81 | 19.32 | 10.24 | 10.98 | CrackPix [16] | 25.18 | 29.33 | 9.57 | 14.69 |
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(Best scores shown in bold font).
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