Opto-Electronic Engineering, Volume. 52, Issue 4, 240295(2025)
YOLOv8-GAIS: improved object detection algorithm for UAV aerial photography
Figures & Tables(15)
Fig. 2. Four-head adaptive multidimensional feature fusion strategy
Fig. 5. Original image and Gamma correction results. (a) Original image; (b) γ'=2.5; (c) γ'=0.7
Fig. 7. Data enhancement visualization results. (a) Original image; (b) Image after translation rotation; (c) Image after HSV adjustment
Fig. 8. Percentage of different categories in the expanded dataset
Fig. 10. Precision-recall curves. (a) YOLOv8s; (b) Image enhancement; (c) Image enhancement and AirNet; (d) Image enhancement, AirNet, and SEAM; (e) Image enhancement, AirNet, SEAM, and FAMFF; (f) Image enhancement, AirNet, SEAM, FAMFF, and InnerSIoU
Fig. 11. Detection results of aerial photography by UAVs at different heights. (a) Aerial photography height of 30 m; (b) Aerial photography height of 60 m; (c) Aerial photography height of 100 m
Table 1. Results of comparison of different models
View tableView in ArticleTable 1. Results of comparison of different models
Model Resolution mAP50/% Pedestrian People Bicycle Car Three-box van Truck Tricycle Awning-tricycle Bus Motor RetinaNet[ 10 ]/ 35.9 27.7 13.5 34.4 54.4 30.6 24.7 25.1 20.1 39.9 25.4 CornetNet[ 10 ]/ 28.1 29.2 18.7 12.8 60.3 33.3 23.9 19.0 12.6 35.9 25.1 CenterNet[ 25 ]/ 26.6 23.1 21.1 15.4 60.6 24.5 21.1 20.3 17.4 38.3 24.4 Faster R-CNN / 33.6 / / / / / / / / / / YOLOv8s 640×640 36.5 37.5 36.8 20.6 61.8 31.8 22.2 45.8 26.3 37.8 52.4 YOLOv5s 864×864 40.3 47.7 49.0 26.4 56.9 39.9 35.2 35.4 25.5 36.5 50.2 YOLOv8-GAIS 640×640 43.2 48.5 55.4 23.8 77.9 39.2 35.4 38.7 24.4 49.4 52.5
Table 2. Results of comparative experiments on different attention mechanisms
View tableView in ArticleTable 2. Results of comparative experiments on different attention mechanisms
Attention mechanism Param/MB GFLOPs /% YOLOv8s 11.23 28.5 36.5 YOLOv8s-CBAM 7.10 24.1 36.8 YOLOv8s-SE 7.05 24.0 37.1 YOLOv8s-SimAM 7.15 23.6 37.3 YOLOv8s-ECA 7.40 23.9 37.8 YOLOv8s-SEAM 7.30 23.9 38.1
Table 3. Results of ablation experiments
View tableView in ArticleTable 3. Results of ablation experiments
YOLOv8s Data enhancement AirNet SEAM FAMFF InnerSIoU Param/MB GFLOPs /% /% Precision/% Recall/% √ 11.23 28.5 36.5 16.8 40.8 33.3 √ √ 11.23 26.3 37.9 18.5 40.4 35.9 √ √ √ 12.50 23.9 39.3 18.7 41.9 35.6 √ √ √ √ 7.30 20.3 38.1 18.5 41.0 35.7 √ √ √ √ √ 8.52 21.7 42.3 21.6 43.6 34.3 √ √ √ √ √ √ 9.70 21.3 43.4 22.4 45.7 35.1
Table 4. Comparison of UAV detection results at different flight altitudes
View tableView in ArticleTable 4. Comparison of UAV detection results at different flight altitudes
Flight altitude/m mAP50/% Awning-tricycle Car Truck 30 39.7 77.1 36.8 60 38.0 77.8 40.2 100 27.1 62.6 25.6
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Kaixuan Li, Xiaofeng Liu, Qiang Chen, Zejiang Zhang. YOLOv8-GAIS: improved object detection algorithm for UAV aerial photography[J]. Opto-Electronic Engineering, 2025, 52(4): 240295
Paper Information
Category: Article
Received: Dec. 17, 2024
Accepted: Mar. 7, 2025
Published Online: Jun. 11, 2025
The Author Email: Xiaofeng Liu (刘晓锋)
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