Optics and Precision Engineering, Volume. 32, Issue 20, 3085(2024)
Integrating global information and dual-domain attention mechanism for optical remote sensing aircraft target detection
Figures & Tables(13)
Fig. 7. Visualization results of different models in complex environments
Fig. 8. Visualization results of different models with small targets
Table 1. Comparison of performance of different spatial pyramid pooling modules
View tableView in ArticleTable 1. Comparison of performance of different spatial pyramid pooling modules
Module Precision Recall mAP50 mAP50-95 Parameters/M FLOPs/B Latency/ms SPP 78.3% 77.2% 83.2% 62.2% 3.01 8.1 0.89 SPPF 81.0% 78.7% 84.6% 63.2% 3.01 8.1 0.88 ASPP 81.5% 77.4% 84.5% 63.2% 3.83 8.7 0.91 RFB 81.1% 77.0% 84.0% 62.8% 3.18 8.2 0.89 SPPCSPC 81.3% 78.1% 84.2% 63.1% 4.62 9.4 0.97 SimCSPSPPF 81.0% 78.1% 84.9% 63.4% 3.36 8.4 0.90 SPPF_Global 82.2% 78.5% 85.6% 64.0% 3.06 8.0 0.88
Table 2. Comparison of performance of different attention mechanisms
View tableView in ArticleTable 2. Comparison of performance of different attention mechanisms
Model Precision Recall mAP50 mAP50-95 Parameters/M FLOPs/B Latency/ms YOLOv8n 81.0% 78.7% 84.6% 63.2% 3.01 8.1 0.88 +CBAM 80.7% 79.0% 84.6% 63.1% 3.08 8.2 0.89 +CA 81.0% 78.4% 84.8% 63.6% 3.02 8.1 0.95 +CPCA 81.5% 78.8% 85.0% 63.6% 3.14 8.3 1.21 +DLKA 82.4% 78.9% 86.0% 64.2% 4.64 9.4 0.90 +EMA 81.9% 76.5% 84.6% 63.3% 3.02 8.2 0.90 +LSKA 80.6% 78.0% 84.8% 63.5% 3.08 8.2 0.89 +SA 80.6% 77.7% 84.8% 63.4% 3.01 8.1 0.89 +SimAM 82.7% 77.3% 85.1% 63.6% 3.01 8.1 0.89 +TA 80.4% 79.1% 85.1% 63.7% 3.01 8.1 0.90 +DDA 81.7% 79.5% 85.9% 64.1% 3.01 8.0 0.88
Table 3. Ablation experiments
View tableView in ArticleTable 3. Ablation experiments
SPPF_
Global
DDA PDS PIoU Precision Recall mAP
50
mAP
50-95
Parameters
/M
FLOPs
/B
Latency
/ms
× × × × 81.0% 78.7% 84.6% 63.2% 3.01 8.1 0.88 √ × × × 82.2% 78.5% 85.6% 64.0% 3.06 8.0 0.88 × √ × × 81.7% 79.5% 85.9% 64.1% 3.01 8.1 0.88 × × √ × 83.1% 78.5% 86.0% 64.6% 2.74 7.8 1.04 √ √ × × 82.6% 79.7% 86.5% 64.6% 3.06 8.0 0.89 √ √ √ × 82.7% 80.8% 87.0% 65.6% 2.81 7.8 1.06 √ √ √ √ 84.3% 81.3% 87.8% 65.8% 2.81 7.8 1.06
Table 4. Comparative experiments on MAR20 dataset
View tableView in ArticleTable 4. Comparative experiments on MAR20 dataset
Model Precision Recall mAP50 mAP50-95 Parameters/M FLOPs/B Latency/ms Faster R-CNN 66.1% 61.1% 80.9% 58.7% 41.75 91.23 8.74 RT-DETR 87.7% 83.4% 83.0% 61.9% 19.9 57.0 4.34 Gold-YOLO-n 78.2% 75.7% 81.8% 59.8% 5.61 12.07 1.35 YOLOv5n 80.6% 75.4% 81.9% 59.6% 1.79 4.2 0.72 YOLOv5s 82.6% 79.5% 85.9% 63.5% 7.06 15.9 1.53 YOLOv6n 79.7% 74.3% 81.9% 59.4% 4.63 11.35 0.99 YOLOv7-tiny 79.9% 75.5% 82.5% 59.5% 6.06 13.2 0.85 YOLOv8n 81.0% 78.7% 84.6% 63.2% 3.01 8.1 0.88 Ours 84.3% 81.3% 87.8% 65.8% 2.81 7.8 1.06
Table 5. Comparative experiments on NWPU VHR-10 dataset
View tableView in ArticleTable 5. Comparative experiments on NWPU VHR-10 dataset
Model Precision Recall mAP50 mAP50-95 Parameters/M FLOPs/B Latency/ms RT-DETR 87.6% 86.3% 88.9% 56.1% 19.88 57.0 4.34 Gold-YOLO 89.9% 79.0% 86.0% 48.2% 5.61 12.06 2.07 YOLOv5n 90.2% 78.6% 86.1% 46.8% 1.77 4.2 1.20 YOLOv5s 92.5% 85.3% 89.6% 51.6% 7.04 15.8 1.79 YOLOv6n 85.2% 80.9% 85.6% 47.7% 4.63 11.34 1.55 YOLOv7-tiny 87.2% 87.0% 89.4% 49.5% 6.03 13.1 2.29 YOLOv8n 86.1% 82.1% 87.7% 54.1% 3.01 8.1 0.87 Ours 91.1% 87.2% 90.2% 54.4% 2.80 7.8 1.05
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Shanling LIN, Xue ZHANG, Yan CHEN, Jianpu LIN, Shanhong LÜ, Zhixian LIN, Tailiang GUO. Integrating global information and dual-domain attention mechanism for optical remote sensing aircraft target detection[J]. Optics and Precision Engineering, 2024, 32(20): 3085
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Received: May. 22, 2024
Accepted: --
Published Online: Jan. 10, 2025
The Author Email: Jianpu LIN (ljp@fzu.edu.cn)
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