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The Role of Deep Learning in Parking Space Identification and Prediction Systems

计算机、材料和连续体（英文） 2023年第4期75卷 761-784页

作者： Faizan Rasheed yasir saleem Kok-Lim Alvin Yau Yung-Wey Chong Sye Loong Keoh School of Physics Engineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Science Aberystwyth UniversityAberystwyth SY233FLUK Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul RahmanKajang43200SelangorMalaysia National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia School of Computing Science University of Glasgow Singapore737729Singapore

In today’s smart city transportation,traffic congestion is a vexing issue,and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40%of traffic *** parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives,resulting in the driver’s frustration and aggravating traffic jams while searching for another parking *** explains the need to predict the availability of parking ***,deep learning(DL)has been shown to facilitate drivers to find parking spaces efficiently,leading to a promising performance enhancement in parking identification and prediction ***,no work reviews DL approaches applied to solve parking identification and prediction *** by this gap,the purpose of this work is to investigate,highlight,and report on recent advances inDLapproaches applied to predict and identify the availability of parking *** of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature,and by doing so,the salient and supportive features of different DL techniques for providing parking solutions are ***,several open research challenges are *** work identifies that there are various DL architectures,datasets,and performance measures used to address parking identification and prediction ***,there are some open-source implementations available that can be used directly either to extend existing works or explore a new *** is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart *** study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits,the convergence of these two types of systems and DL brings about new i

关键词： Convolutional neural network deep learning neural networks parking identification parking prediction smart city

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