Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches.
Video Based Machine Learning for Traffic Intersections describes the development of computer vision and machine learning-based applications for Intelligent Transportation Systems (ITS) and the challenges encountered during their deployment. This book presents several novel approaches.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Tania Banerjee, PhD, is a research assistant scientist in Computer and Information Science and Engineering at the University of Florida. She earned her PhD in Computer Science from the University of Florida in 2012. She completed her MSc in Mathematics from the Indian Institute of Technology, Kharagpur. Her research interests are video analytics, intelligent transportation, data compression, and high performance computing. Xiaohui Huang, PhD, earned her PhD in the Department of Computer & Information Science & Engineering, University of Florida, Gainesville, Florida, in December, 2020. Her research interests include machine learning, computer vision, and intelligent transportation systems. Aotian Wu is currently a PhD student in the Department of Computer & Information Science & Engineering, University of Florida, Gainesville, Florida. Her research interests are machine learning, computer vision, and intelligent transportation systems. Ke Chen is currently a PhD student in the Department of Computer & Information Science & Engineering, University of Florida, Gainesville, Florida. His research interests are machine learning, computer architecture, operating systems and algorithms, and data structures. Anand Rangarajan, PhD, is a Professor, Department of CISE, University of Florida. His research interests are machine learning, computer vision, medical and hyperspectral imaging, and the science of consciousness. Sanjay Ranka, PhD, is a Distinguished Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are high performance computing and big data science with a focus on applications in CFD, healthcare and transportation. He has co-authored four books and 290+ journal and refereed conference articles. He is a Fellow of the IEEE and AAAS. He is an Associate Editor-in-Chief of the Journal of Parallel and Distributed Computing and an Associate Editor for ACM Computing Surveys, Applied Sciences, Applied Intelligence, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
Inhaltsangabe
1. Introduction 2. Detection, Tracking, and Classification 3. Near miss Detection 4. Severe Events 5. Performance Safety Trade offs 6. Trajectory Prediction 7. Vehicle Tracking across Multiple Intersections 8. User Interface 9. Conclusion
