METHODOLOGY FOR ASSESSING TRAFFIC INTENSITY ON THE BASIS OF VIDEO SURVEILLANCE DATA

O. Lebedeva, Ekaterina Savvateeva
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Abstract

The paper presents an approach to intelligent transport systems based on advanced machine learning algorithms, the purpose of which is to estimate the traffic flow on the road network. Data is obtained from traffic cameras located in a limited number of places. The approach includes two main algorithms. The first is a probabilistic algorithm for counting vehicles from low-quality images, which belongs to the category of unsupervised learning
基于视频监控数据的交通强度评估方法
本文提出了一种基于先进机器学习算法的智能交通系统方法,其目的是估计道路网络上的交通流量。数据是从位于有限地方的交通摄像头获得的。该方法包括两个主要算法。首先是一种从低质量图像中统计车辆的概率算法,属于无监督学习的范畴
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