Intelligent Vehicle Automatic Identification System Based on YOLOv4 and ViSLAM

Chenzhi Nie, Wei-teng Lin, Xiuwen Zheng
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Abstract

In this paper, we use intelligent vehicles as the platform and use convolutional neural networks for lane recognition and classification during driving. For the recognition of landmarks, we use YOLOv4, a popular YOLO series algorithm, as the model for recognition. At the same time, we study and explore intelligent vehicle mapping and positioning technology based on the SLAM framework in a laboratory working environment with weak signals.
基于YOLOv4和ViSLAM的智能车辆自动识别系统
本文以智能汽车为平台,利用卷积神经网络进行车道识别和分类。对于地标的识别,我们使用流行的YOLO系列算法YOLOv4作为识别模型。同时,在实验室弱信号工作环境下,研究探索基于SLAM框架的智能车辆测绘定位技术。
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