Small target detection algorithm for flapping wing UAV based on improved YOLOv8

Chen Ma; Ketao Du; Askar Hamdulla

doi:10.1117/12.2683452

26 June 2023 Small target detection algorithm for flapping wing UAV based on improved YOLOv8

Chen Ma, Ketao Du, Askar Hamdulla

Proceedings Volume 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023); 127211O (2023) https://doi.org/10.1117/12.2683452
Event: 2023 2nd International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2023, Chengdu, China

Abstract

This paper proposes an algorithm based on an improved version of YOLOv8l, which is designed for small target detection on flapping wing drones. By adding a small object detection layer and introducing Multi-head self-attention (MHSA), the algorithm effectively reduces interference from irrelevant backgrounds and enhances the network's feature extraction performance. Experimental results on both the flapping wing dataset and the VisDrone dataset demonstrate that compared with the baseline YOLOv8l algorithm, the improved algorithm shows a 4.1% and 3.3% improvement in the mAP@.5 and mAP@.5:.95 indicators, respectively, and a 5.9% and 4% improvement on the VisDrone dataset. Particularly noteworthy is the improved algorithm's performance on the mAP@.5 index, which achieved 50.1% on the VisDrone dataset, proving its robustness and exceptional performance in small target detection. These results illustrate the algorithm's effectiveness and practicality, making it a valuable tool for flapping wing UAV vision applications.

Citation Download Citation

Chen Ma, Ketao Du, and Askar Hamdulla "Small target detection algorithm for flapping wing UAV based on improved YOLOv8", Proc. SPIE 12721, Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 127211O (26 June 2023); https://doi.org/10.1117/12.2683452

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KEYWORDS

Object detection

Target detection

Detection and tracking algorithms

Small targets

Unmanned aerial vehicles

Feature extraction

Visual process modeling

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