Study on automatic target identification method in substation 3D scene model
, , , oraz
25 wrz 2025
O artykule
Data publikacji: 25 wrz 2025
Otrzymano: 01 lut 2025
Przyjęty: 09 maj 2025
DOI: https://doi.org/10.2478/amns-2025-1009
Słowa kluczowe
© 2025 Youhui Chen et al., published by Sciendo.
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.

Figure 2.

Figure 3.

Performance comparison of different algorithms
| Model | mAP@0.5/% | mAP@0.5:0.95/% | Vol/MB | FPS/(f/s) |
|---|---|---|---|---|
| YOLOv5n | 84.62 | 59.08 | 3.88 | 139 |
| YOLOv5s | 87.85 | 63.92 | 14.45 | 125 |
| YOLOv5m | 88.89 | 66.63 | 42.54 | 95 |
| YOLOv5l | 89.15 | 67.25 | 93.81 | 80 |
| YOLOv5x | 89.64 | 67.41 | 175.29 | 55 |
| YOLOv3 | 81.82 | 46.34 | 246.64 | 43 |
| YOLOv4 | 82.06 | 47.49 | 256.41 | 35 |
| YOLOXs | 81.38 | 50.88 | 36.64 | 32 |
| SSD | 40.54 | 20.25 | 98.58 | 43 |
| Faster RCNN | 50.29 | 23.21 | 115.37 | 15 |
| Ours | 90.37 | 68.94 | 8.72 | 92 |
Comparison of the results of the drop sampling experiment
| Method | The number of original clouds | The number of clouds in the back point | Time(s) |
|---|---|---|---|
| Random drop sampling | 281421 | 47251 | 0.1274 |
| Uniform drop sampling | 281421 | 47251 | 0.1532 |
| Body drop sampling | 281421 | 47251 | 0.1049 |
RMSE and time-consuming comparison results of different algorithms
| No. | ICP | RANSAC+ICP | Ours | |||
|---|---|---|---|---|---|---|
| 1 | RMSE | Time/s | RMSE | Time/s | RMSE | Time/s |
| 2 | 0.632 | 0.159 | 0.385 | 0.253 | 0.079 | 0.275 |
| 3 | 0.683 | 0.214 | 0.465 | 0.276 | 0.075 | 0.318 |
| 4 | 0.652 | 0.208 | 0.472 | 0.295 | 0.077 | 0.299 |
| 5 | 0.637 | 0.201 | 0.516 | 0.282 | 0.076 | 0.273 |
| 6 | 0.601 | 0.311 | 0.243 | 0.674 | 0.019 | 0.615 |
| 7 | 0.641 | 0.374 | 0.357 | 0.645 | 0.008 | 0.649 |
| 8 | 0.648 | 0.459 | 0.551 | 1.142 | 0.009 | 1.106 |
| 9 | 0.639 | 0.428 | 0.538 | 0.938 | 0.013 | 0.627 |
| 10 | 0.655 | 0.417 | 0.492 | 0.729 | 0.007 | 1.235 |
Improve the lateral contrast experiment of the module
| Model | mAP@0.5/% | mAP@0.5:0.95/% | Model | mAP@0.5/% | mAP@0.5:0.95/% |
|---|---|---|---|---|---|
| YOLOv5 | 49.84 | 30.49 | FPN | 49.84 | 30.49 |
| SE | 50.69 | 32.95 | PANet | 51.06 | 32.95 |
| BAM | 50.93 | 33.41 | GFPN | 51.98 | 33.16 |
| CBAM | 51.42 | 33.87 | PRFPN | 52.31 | 33.83 |
| CAM | BIFPN | ||||
| Model | Loss value | mAP@0.5/% | Model | Loss value | mAP@0.5/% |
| IoU | 0.0712 | 60.52 | EIoU | 0.0691 | 64.27 |
| GIoU | 0.0694 | 63.45 | SIoU | 0.0685 | 64.41 |
| DIoU | 0.0695 | 62.93 | CIoU |
Removal experiment from the group point
| Method | Parameter | Drop sampling | Removal from the group point | Time(s) |
|---|---|---|---|---|
| Radius filtering | 47251 | 47179 | 0.1042 | |
| 47251 | 47103 | 0.1225 | ||
| 47251 | 47192 | 0.1563 | ||
| Statistical filtering | 47251 | 46935 | 0.0991 | |
| 47251 | 46326 | 0.1208 | ||
| 47251 | 45834 | 0.1517 |
The experimental results of the model
| Group | BiFPN | CAM | CIoU | Vol/MB | FPS/(f/s) | mAP@0.5/% | mAP@0.5:0.95/% |
|---|---|---|---|---|---|---|---|
| 1 | × | × | × | 14.45 | 125 | 87.85 | 63.92 |
| 2 | √ | × | × | 13.98 | 103 | 87.94 | 64.06 |
| 3 | × | √ | × | 12.07 | 101 | 88.06 | 64.73 |
| 4 | × | × | √ | 14.45 | 125 | 87.85 | 63.92 |
| 5 | √ | √ | × | 11.39 | 100 | 88.74 | 65.97 |
| 6 | √ | × | √ | 13.98 | 98 | 89.23 | 66.48 |
| 7 | × | √ | √ | 10.86 | 95 | 89.62 | 67.81 |
| 8 | √ | √ | √ | 8.72 | 92 | 90.37 | 68.94 |
