NEURAL NETWORK BASED IMAGE RECOGNITION METHOD FOR SMART PARKING

Olga Pavlova, Volodymyr Kovalenko, T. Hovorushchenko, Volodymyr Avsiyevych
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引用次数: 1

Abstract

With the exponential growth of vehicles on our streets, the need for finding an unoccupied parking spot today could most of the time be problematic, but even more in the coming future. Smart parking solutions have proved to be a helpful approach to facilitate the localization of unoccupied parking spots. In many smart parking solutions, sensors are used to determine the vacancy of a parking spot. i.e use of sensors can provide a highly accurate solution in terms of determining the status of parking lots. However, this is not ideal from a scalability point of view, since the need for installing and maintaining each of the sensors is not considered cost-effective. In the latest years vision based solutions have been considered more when building a smart parking solution, since cameras can easily be installed and used on a large parking area. Furthermore, the use of cameras can provide more advanced solution for finding a vacant parking spot and also for providing the safety of the car on the public parking area. This paper is aimed at the developing a Neural-Network based Image Recognition Method for Smart Parking.
基于神经网络的智能停车图像识别方法
随着街道上的车辆呈指数级增长,在今天的大多数时间里,寻找一个空置的停车位可能是一个问题,但在不久的将来,这个问题会更加严重。智能停车解决方案已被证明是一种有效的方法,可以促进空置停车位的定位。在许多智能停车解决方案中,传感器用于确定停车位的空缺。也就是说,传感器的使用可以提供一个高度精确的解决方案,以确定停车场的状态。然而,从可扩展性的角度来看,这并不理想,因为安装和维护每个传感器的需求被认为是不划算的。近年来,基于视觉的解决方案在构建智能停车解决方案时得到了更多的考虑,因为摄像头可以很容易地在大型停车场安装和使用。此外,摄像头的使用可以为寻找空置停车位提供更先进的解决方案,也可以为公共停车场的汽车提供安全保障。本文旨在开发一种基于神经网络的智能停车图像识别方法。
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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