August 15, 2025SensorsOpen Access

I-YOLOv11n: A Lightweight and Efficient Small Target Detection Framework for UAV Aerial Images

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Detection accuracy of small targets is effectively improved while maintaining real-time capabilities with the I-YOLOv11n framework.
Model parameter size reduced to 3.87 M and computation lowered to 14.7 GFLOPs, enhancing efficiency.
Approach utilizes a collaborative lightweight strategy with knowledge distillation and pruning mechanisms for optimal performance.
Experiments on multiple datasets show remarkable improvements in mAP scores compared to the benchmark YOLOv11n model.

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Lightweight framework improves small target detection accuracy in UAV images, suggesting better deployment adaptability.

Ma et al. (2025) studied this question.

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