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Published in:
2023 | OriginalPaper | Chapter
Aircraft Target Detection Algorithm Based on Improved YOLOv5s
Authors : Lixia Zhang, Zhiming Ma, Xiangshu Peng, Menglin Qi
Published in: Artificial Intelligence in China
Publisher: Springer Nature Singapore
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Abstract
Aiming at the characteristics of multi-scale, diversity and complex background of aircraft targets, in order to improve the average detection accuracy of YOLOv5s algorithm, an improved aircraft target detection algorithm based on YOLOv5s model is proposed, Firstly, replace conv module in the backbone network of YOLOv5s with RepVGGBlock to reduce the number of parameters; Secondly, a small target detection head is added to enhance the recognition ability of small targets; Finally, GAM_Attention mechanism is introduced in front of each detection head to improve the detection accuracy. The research shows that the RG-YOLOv5s (Repvggblock GAM_Attention you only look once) algorithm proposed in this paper improves the average accuracy by about 1% and reaches 97.3% when IOU = 0.5, which is more suitable for the detection of aircraft remote sensing targets.