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020			_a9783030656614
024	7		_a10.1007/978-3-030-65661-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTE228.3 _b2021 EB
245	1	0	_aDeep Learning and Big Data for Intelligent Transportation : _bEnabling Technologies and Future Trends _cedited by Khaled R. Ahmed, Aboul Ella Hassanien.
250			_aFirst edition 2021
264		1	_aCham _bSpringer International Pulishing _c2021
300			_a1 recurso en línea (X, 264 páginas) _b130 ilustraciones, 102 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aStudies in Computational Intelligence _x1860-9503 _v945
490	0		_aIntelligent Technologies and Robotics (SpringerNature-42732)
490	0		_aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505	0		_aPart I: Big Data and Autonomous Vehicles -- Big Data Technologies with Computanational Model Computing using HADOOP with Scheduling Challeges -- Big Data for Autonomous Vehicles -- Part II: Deep Learning &Object detection for Safe driving -- Analysis of Target Detection and Tracking for Intelligent Vision System -- Enhanced end-to-end system for autonomous driving using deep convolutional networks.-Deep Learning Technologies to mitigate Deer-Vehicle Collisions -- Night-to-Day Road Scene Translation Using Generative Adversarial Network with Structural Similarity Loss for Night Driving Safety -- Safer-Driving: Application of Deep Transfer Learning to Build Intelligent Transportation Systems -- Leveraging CNN Deep Learning Model for Smart Parking -- Estimating Crowd Size for Public Place Surveillance using Deep Learning -- Part III: AI & IoT for intelligent transportation -- IoT Based Regional Speed Restriction Using Smart Sign Boards -- Synergy of Internet of Things with Cloud, Artificial Intelligence and Blockchain for Empowering Autonomous Vehicles -- Combining Artificial Intelligence with Robotic Process Automation - An Intelligent Automation Approach.
520	3		_aThis book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today's technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle's speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.
988			_aSpringer_Robotics_2021
650		7	_2embne _9147646 _aSistemas de comunicación móviles
700	1		_aAhmed, Khaled R. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681902
700	1		_aHassanien, Aboul-Ella _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _997150
776	0	8	_iPrinted edition: _z9783030656607
776	0	8	_iPrinted edition: _z9783030656621
776	0	8	_iPrinted edition: _z9783030656638
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-65661-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE