Review of Lightweight Target Detection Algorithms

YE Baicheng; ZHU Youpan; ZHOU Yongkang; DUAN Chenhao; ZHANG Yudong; TAO Zhigang; FU Zhiyu

Volume 47 Issue 3

Mar. 2025

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Infrared Technology > 2025 > 47(3): 289-298.

YE Baicheng, ZHU Youpan, ZHOU Yongkang, DUAN Chenhao, ZHANG Yudong, TAO Zhigang, FU Zhiyu. Review of Lightweight Target Detection Algorithms[J]. Infrared Technology , 2025, 47(3): 289-298.

Citation:

YE Baicheng, ZHU Youpan, ZHOU Yongkang, DUAN Chenhao, ZHANG Yudong, TAO Zhigang, FU Zhiyu. Review of Lightweight Target Detection Algorithms[J]. Infrared Technology , 2025, 47(3): 289-298.

Citation:

YE Baicheng, ZHU Youpan, ZHOU Yongkang, DUAN Chenhao, ZHANG Yudong, TAO Zhigang, FU Zhiyu. Review of Lightweight Target Detection Algorithms[J]. Infrared Technology , 2025, 47(3): 289-298.

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Review of Lightweight Target Detection Algorithms

YE Baicheng^1,,
ZHU Youpan^{1, 2, ,},
ZHOU Yongkang^{1, 2, 3},
DUAN Chenhao^{2, 4},
ZHANG Yudong¹,
TAO Zhigang^{1, 2},
FU Zhiyu^{1, 2}

1.
Kunming Institute of Physics, Kunming 650223, China
2.
Yunnan Key Laboratory of Low-light-level Night Vision Detection and Intelligent Visual Navigation, Kunming 650223, China
3.
School of Life Sciences, Beijing Institute of Technology, Beijing 100081, China
4.
North Optoelectronic Instrument Co., Ltd., Kunming 650114, China

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Received Date: December 05, 2023
Revised Date: January 23, 2024

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Abstract

Abstract

Traditional target detection algorithms based on deep learning usually require extensive computing resources and long-term training, which do not meet the needs of the industry. Lightweight target detection networks sacrifice part of the detection accuracy in exchange for faster inference speed and lighter models. They are suitable for applications in edge-computing devices and have received widespread attention. This study introduces lightweight technologies commonly used to compress and accelerate models, classifies and analyzes the structural principles of lightweight backbone networks, and evaluates their practical impact on YOLOv5s. Finally, the prospects and challenges of lightweight target-detection algorithms are discussed.
- deep learning,
- target detection,
- lightweight technology,
- backbone network

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References (64)

References

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