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Titlebook: Traffic Mining Applied to Police Activities; Proceedings of the 1 Fabio Leuzzi,Stefano Ferilli Conference proceedings 2018 Springer Interna

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書目名稱Traffic Mining Applied to Police Activities
副標題Proceedings of the 1
編輯Fabio Leuzzi,Stefano Ferilli
視頻videohttp://file.papertrans.cn/928/927545/927545.mp4
概述Gathers the proceedings of the 1st Italian Conference for the Traffic Police, Rome, Italy, October 25-26, 2017.Aimed at researchers as well as practitioners, standard developers and policymakers.Prese
叢書名稱Advances in Intelligent Systems and Computing
圖書封面Titlebook: Traffic Mining Applied to Police Activities; Proceedings of the 1 Fabio Leuzzi,Stefano Ferilli Conference proceedings 2018 Springer Interna
描述.This book presents high-quality original contributions on the development of automatic traffic analysis systems that are able to not only anticipate traffic scenarios, but also understand the behavior of road users (vehicles, bikes, trucks, etc.) in order to provide better traffic management, prevent accidents and, potentially, identify criminal behaviors. Topics also include traffic surveillance and vehicle accident analysis using formal concept analysis, convolutional and recurrent neural networks, unsupervised learning and process mining. The content is based on papers presented at the 1st Italian Conference for the Traffic Police (TRAP), which was held in Rome in October 2017. This conference represents a targeted response to the challenges facing the police in connection with managing massive traffic data, finding patterns from historical datasets, and analyzing complex traffic phenomena in order to anticipate potential criminal behaviors. The book will appeal to researchers, practitioners and decision makers interested in traffic monitoring and analysis, traffic modeling and simulation, mobility and social data mining, as well as members of the police..
出版日期Conference proceedings 2018
關鍵詞Traffic Surveillance; Vehicle Accident Analysis; Traffic Classification; Data Traffic Analysis; Traffic
版次1
doihttps://doi.org/10.1007/978-3-319-75608-0
isbn_softcover978-3-319-75607-3
isbn_ebook978-3-319-75608-0Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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