Research on Complex Environment Adaptation Technology and Its Algorithm for Intelligent Networked Vehicles
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17 mar 2025
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Publicado en línea: 17 mar 2025
Recibido: 17 oct 2024
Aceptado: 26 ene 2025
DOI: https://doi.org/10.2478/amns-2025-0192
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© 2025 Fan Luo et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Test results of YOLOv5s model on BDD100K dataset
Class | Images | Labels | P/% | R/% | mAP@0.5/% |
---|---|---|---|---|---|
All | 4000 | 10399 | 84.27 | 83.93 | 85.05 |
Car | 1000 | 9321 | 92.57 | 90.18 | 91.95 |
Truck | 1000 | 254 | 85.92 | 81.62 | 83.69 |
Pedestrian | 1000 | 372 | 86.53 | 87.20 | 84.33 |
Cyclist | 1000 | 452 | 83.85 | 85.15 | 82.79 |
Test results of YOLOv5s-CBC model on BDD100K dataset
Class | Images | Labels | P/% | R/% | mAP@0.5/% |
---|---|---|---|---|---|
All | 4000 | 10399 | 89.42 | 88.9 | 90.68 |
Car | 1000 | 9321 | 95.61 | 94.08 | 93.59 |
Truck | 1000 | 254 | 90.92 | 88.52 | 87.64 |
Pedestrian | 1000 | 372 | 89.43 | 91.75 | 89.59 |
Cyclist | 1000 | 452 | 86.47 | 89.61 | 86.61 |