YOLO系列目标检测模型发展规律与未来演进方向研究

刘思佳; 黄军峰; 李煜晨; 李发旗; 许惠美

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汽车电器 ›› 2025, Vol. 1 ›› Issue (11) : 67-69.

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YOLO系列目标检测模型发展规律与未来演进方向研究

刘思佳, 黄军峰, 李煜晨, 李发旗, 许惠美

作者信息 +

Research on the Development Law and Future Evolution Direction of YOLO Series Object Detection Model

Liu Sijia, Huang Junfeng, Li Yuchen, Li Faqi, Xu Huimei

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文章历史 +

摘要

YOLO系列模型是单阶段目标检测代表性算法,自2016年提出后历经五次重大迭代。本文系统分析YOLOv1至v5技术演进路径,从网络架构设计、损失函数优化、特征融合策略等维度提炼发展规律,结合当前技术趋势为其未来发展提出建议。

Abstract

The YOLO series model is a representative algorithm for single-stage object detection, and it has undergone five major iterations since it was proposed in 2016. This paper systematically analyzes the technical evolution path of YOLO v1 to v5, and summarizes the development laws from the dimensions of network architecture design, loss function optimization and feature fusion strategy. Suggestions for its future development are put forward in combination with the current technical trend.

导出引用

刘思佳, 黄军峰, 李煜晨, 李发旗, 许惠美. YOLO系列目标检测模型发展规律与未来演进方向研究[J]. 汽车电器. 2025, 1(11): 67-69

Liu Sijia, Huang Junfeng, Li Yuchen, Li Faqi, Xu Huimei. Research on the Development Law and Future Evolution Direction of YOLO Series Object Detection Model[J]. AUTO ELECTRIC PARTS. 2025, 1(11): 67-69

中图分类号： U463.6

参考文献

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