车辆自动驾驶中MSPRN目标识别算法的设计

Min Yang
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引用次数: 1

摘要

车辆自动驾驶技术可以有效地提高车辆行驶的安全性能。本研究就是为了满足车辆自动驾驶的需要,提出一种性能更好的目标识别算法。根据已有研究,在传统Faster R-CNN算法的基础上对算法进行了优化和改进,提出了一种基于Multi Strategy region candidate box的网络目标识别算法,对锚盒进行了优化。通过对比分析传统R-CNN算法与MSPRN算法的识别率和召回率,可以看出MSPRN算法具有更好的算法性能,适用于车辆自动驾驶中的目标检测和识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of MSPRN Target Recognition Algorithm for Vehicle Automatic Driving
Vehicle automatic driving technology can effectively improve the safety performance of vehicle driving. This research is to meet the needs of vehicle automatic driving, and propose a target recognition algorithm with better performance. According to the existing research, the algorithm is optimized and improved based on the traditional Faster R-CNN algorithm, and a network target recognition algorithm based on Multi Strategy Regional candidate box is proposed to optimize the anchor box. Through the comparative analysis of recognition and recall rate between traditional R-CNN algorithm and MSPRN algorithm, it can be seen that MSPRN algorithm has better algorithm performance and is suitable for target detection and recognition in vehicle automatic driving.
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