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Author: Biswajeet Pradhan
Publisher: Springer
ISBN: 3030103749
Category : Technology & Engineering
Languages : en
Pages : 165
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Book Description
This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.
Author: Biswajeet Pradhan
Publisher: Springer
ISBN: 3030103749
Category : Technology & Engineering
Languages : en
Pages : 165
Get Book Here
Book Description
This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.
Author: Biswajeet Pradhan
Publisher:
ISBN: 9783030103750
Category : Optical radar
Languages : en
Pages : 157
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Book Description
This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.
Author: Yu-Chen Hu
Publisher: Springer Nature
ISBN: 9811679525
Category : Technology & Engineering
Languages : en
Pages : 620
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Book Description
This book features high-quality, peer-reviewed papers from the Fourth International Conference on Recent Advancements in Computer, Communication, and Computational Sciences (RACCCS 2021), held at Aryabhatta College of Engineering and Research Center, Ajmer, India, on August 20–21, 2021. Presenting the latest developments and technical solutions in computational sciences, it covers a variety of topics, such as intelligent hardware and software design, advanced communications, intelligent computing technologies, advanced software engineering, the web and informatics, and intelligent image processing. As such, it helps those in the computer industry and academia to use the advances in next-generation communication and computational technology to shape real-world applications.
Author: M. Afshar Alam
Publisher: European Alliance for Innovation
ISBN: 163190292X
Category : Social Science
Languages : en
Pages : 606
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Book Description
The International Conference on ICT for Digital, Smart, and Sustainable Development (ICIDSSD’20) aims to provide an annual platform for the researchers, academicians, and professionals from across the world. ICIDSSD’20, held at Jamia Hamdard, New Delhi, India, is the second international conference of this series of conferences to be held annually. The conference majorly focuses on the recent developments in the areas relating to Information and Communication Technologies and contributing to Sustainable Development. ICIDSSD’20 has attracted research papers pertaining to an array of exciting research areas. The selected papers cover a wide range of topics including but not limited to Sustainable Development, Green Computing, Smart City, Artificial Intelligence, Big Data, Machine Learning, Cloud Computing, IoT, ANN, Cyber Security, and Data Science. Papers have primarily been judged on originality, presentation, relevance, and quality of work. Papers that clearly demonstrate results have been preferred. We thank our esteemed authors for having shown confidence in us and entrusting us with the publication of their research papers. The success of the conference would not have been possible without the submission of their quality research works. We thank the members of the International Scientific Advisory Committee, Technical Program Committee and members of all the other committees for their advice, guidance, and efforts. Also, we are grateful to our technical partners and sponsors, viz. HNF, EAI, ISTE, AICTE, IIC, CSI, IETE, Department of Higher Education, MHRD and DST for sponsorship and assistance.
Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3031184610
Category : Technology & Engineering
Languages : en
Pages : 948
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Book Description
The seventh Future Technologies Conference 2022 was organized in a hybrid mode. It received a total of 511 submissions from learned scholars, academicians, engineers, scientists and students across many countries. The papers included the wide arena of studies like Computing, Artificial Intelligence, Machine Vision, Ambient Intelligence and Security and their jaw- breaking application to the real world. After a double-blind peer review process 177 submissions have been selected to be included in these proceedings. One of the prominent contributions of this conference is the confluence of distinguished researchers who not only enthralled us by their priceless studies but also paved way for future area of research. The papers provide amicable solutions to many vexing problems across diverse fields. They also are a window to the future world which is completely governed by technology and its multiple applications. We hope that the readers find this volume interesting and inspiring and render their enthusiastic support towards it.
Author: Han Qiu
Publisher: Springer Nature
ISBN: 3030821536
Category : Computers
Languages : en
Pages : 704
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Book Description
This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021. The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.
Author:
Publisher:
ISBN:
Category : Automobiles
Languages : en
Pages : 132
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Book Description
Author: Michael James Olsen
Publisher: Transportation Research Board
ISBN: 0309259142
Category : Highway planning
Languages : en
Pages : 208
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Book Description
" TRB's National Cooperative Highway Research Program (NCHRP) Report 748: Guidelines for the Use of Mobile LIDAR in Transportation Applications presents guidelines for the application of mobile 3D light detection and ranging (LIDAR) technology to the operations of state departments of transportation. Mobile LIDAR uses laser scanning equipment mounted on vehicles in combination with global positioning systems (GPS) and inertial measurement units (IMU) to rapidly and safely capture large datasets necessary to create highly accurate, high resolution digital representations of roadways and their surroundings. " -- Publisher's description.
Author:
Publisher:
ISBN:
Category : Weights and measures
Languages : en
Pages : 752
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Book Description
Author: United States. National Bureau of Standards
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 620
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Book Description
