Development of an Application for Vehicle Classification Using Neural Networks Technologies

V. Varkentin, Dmitrii Kolobanov
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引用次数: 3

Abstract

Nowadays, millions of people use the car as a mean of transport on a daily basis, whether it is taxi or personal transport. The automotive industry is actively developing, and more people are using the products of their activities. The number of car owners is increasing every day. Statistics show that every hour a new driver moves out in a brand new car. Detection of vehicles, mentioning categories of video data sequence, is an important but challenging task in terms of observing city traffic. The main difficulty of this task is that it requires the accurate localization of relatively small vehicles in complex scenes and must detect them in real time. The paper discusses the development of an application for the classification of vehicles in a video stream using neural network technologies.
基于神经网络技术的车辆分类应用开发
如今,数以百万计的人每天使用汽车作为交通工具,无论是出租车还是私人交通工具。汽车工业正在积极发展,越来越多的人正在使用他们活动的产品。汽车拥有者的数量每天都在增加。统计数据显示,每小时就有一位新司机开着一辆崭新的汽车出来。在城市交通观测中,车辆检测是一项重要但具有挑战性的任务,涉及视频数据序列的类别。该任务的主要难点在于需要对复杂场景中相对较小的车辆进行精确定位,并且必须实时检测。本文讨论了一种基于神经网络技术的视频流车辆分类应用的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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