Table 5 Performance comparison of the proposed model and previous studies in terms of \(r^2\), AAE, and ASE.
From: An intelligent YOLO and CNN-BiGRU framework for road infrastructure based anomaly assessment
Model | \(\varvec{r}^\textbf{2} \mathbf{(Mean} \varvec{\pm } \mathbf{SD)}\) | AAE (Mean \(\varvec{\pm }\) SD) | ASE (Mean \(\varvec{\pm }\) SD) |
|---|---|---|---|
Luo et al.36 | 0.50 ± 0.11 | 0.75 ± 0.59 | 0.78 ± 0.89 |
Zhang et al.37 | 0.57 ± 0.17 | 0.73 ± 0.08 | 0.68 ± 0.28 |
Rathee et al.38 | 0.67 ± 0.73 | 0.71 ± 0.04 | 0.78 ± 0.85 |
Proposed model | 0.77 \(\varvec{\pm }\) 0.77 | 0.31 \(\varvec{\pm }\) 0.01 | 0.34 \(\varvec{\pm }\) 0.13 |
