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UAV image object recognition method based on small sample learning

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Abstract

In recent years, unmanned aerial vehicles (UAVs) have developed rapidly. Because of their small size, low cost, and strong maneuverability, they have been widely used in several fields such as aerial photography, rescue, transportation, and agriculture. Object recognition requires a large amount of data, but in real application scenarios, due to factors such as privacy and high data labeling costs, it is impossible to obtain sufficient label training samples. This paper proposes an unmanned aerial vehicle (UAV) image object recognition model based on small sample learning (IORS). Based on data enhancement and improved feature fusion capabilities, the YOLOv4_Tiny model is improved to make it more applicable to UAV images. This solves the problem of identifying dense small targets in UAV images when dealing with a small number of samples. The experimental results showed that in UAV images, the proposed method has a good target recognition effect without reducing the speed, while the overall accuracy is increased by approximately 4.5%.

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Data availability

The datasets analysed during the current study are available in the [VisDrone] repository, [http://aiskyeye.com/].

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Acknowledgements

This research was funded by the Natural Science Foundation of Chongqing (CSTB2022NSCQ-MSX1415) and the National Natural Science Foundation of China (61702020).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Beijing Technology and Business University, No. 11 Fucheng Road, Haidian District, Beijing, China, 100048

    Li Tan, Xinyue Lv & Ge Wang

  2. Chongqing Institute of Microelectronics Industry Technology, University of Electronic Science and Technology of China, Unit 3, Building 1, Phase III, R&D Building, Xiyong Microelectronics Park, Shapingba District, 401331, Chongqing, China

    Li Tan

  3. School of Artificial Intelligence, Beijing Technology and Business University, No. 11 Fucheng Road, Haidian District, Beijing, China, 100048

    Xiaofeng Lian

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  1. Li Tan
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  2. Xinyue Lv
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Correspondence to Li Tan.

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Tan, L., Lv, X., Wang, G. et al. UAV image object recognition method based on small sample learning. Multimed Tools Appl 82, 26631–26642 (2023). https://doi.org/10.1007/s11042-023-14985-y

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  • DOI: https://doi.org/10.1007/s11042-023-14985-y

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