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Pedestrian detection algorithm based on improved Yolo v3

机译:基于改进的YOLO V3的行人检测算法

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Pedestrian detection has always been a research hotspot and difficulty in the field of video analysis, and it has a wide range of applications in fields such as unmanned driving, road monitoring, and smart cities. Aiming at this problem, a pedestrian detection method based on the improved YOLOv3 algorithm is proposed. The software system is implemented and verified based on YOLO v3. Experimental results show that in pedestrian detection data sets such as the INRIA pedestrian data set, the accuracy of the algorithm is improved by 6.3% compared with the original algorithm. The target detection technology can meet the real-time performance and test requirements in terms of pedestrian accuracy. Finally, the future development and further research directions of pedestrian detection technology are discussed.
机译:行人检测始终是视频分析领域的研究热点和困难,它在诸如无人驾驶,道路监控和智能城市等领域拥有广泛的应用。 针对这个问题,提出了一种基于改进的YOLOV3算法的行人检测方法。 基于YOLO V3实现和验证软件系统。 实验结果表明,在诸如Inria行人数据集的行人检测数据集中,与原始算法相比,算法的准确性提高了6.3%。 目标检测技术可以在行人精度方面满足实时性能和测试要求。 最后,讨论了人行道检测技术的未来发展和进一步的研究方向。

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