Publication: DCAS-EMAdp: Small Space Object Detection with Lightweight DCAS and Directional-Pooling Enhanced EMA
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Issued Date
2025-01-01
Resource Type
Scopus ID
2-s2.0-105032736566
Journal Title
Icsec 2025 29th International Computer Science and Engineering Conference 2025
Start Page
273
End Page
280
Rights Holder(s)
SCOPUS
Bibliographic Citation
Icsec 2025 29th International Computer Science and Engineering Conference 2025 (2025) , 273-280
Suggested Citation
Nuamnoi P., Thammasudjarit R., Khonthapagdee S., Tanirat P., Channumsin S., Thongsuwan S. DCAS-EMAdp: Small Space Object Detection with Lightweight DCAS and Directional-Pooling Enhanced EMA. Icsec 2025 29th International Computer Science and Engineering Conference 2025 (2025) , 273-280. 280. doi:10.1109/ICSEC67360.2025.11298118 Retrieved from: https://hdl.handle.net/20.500.14740/55395
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Abstract
Small Space Object Detection is a key component of Space Situational Awareness (SSA), which is essential for tracking and detecting fast-moving small space objects under complex environments. A major drawback is that detection models often cannot preserve the structural and contextual details of small or occluded objects. To address this problem, we propose a model named DCAS-EMAdp model, which combines a Dynamic Context-Aware Aggregation Strategy (DCAS) to dynamically expand the receptive field with an Efficient Multi-Scale Attention with Directional Pooling (EMAdp) module to enhance directional feature learning. The model is evaluated using real observational data obtained from the Geo-Informatics and Space Technology Development Agency (GISTDA), captured through ground-based telescope systems for space object monitoring. The experimental results show that DCAS-EMAdp achieves an mAP@50 of 91.4%. Furthermore, evaluations on mAP50@95, Precision, Recall, and F1-score confirm that DCAS-EMAdp has high capabilities in detecting small space object detection and occluded objects, and its performance is sufficient for practical applications in resource-constrained real-Time SSA systems.