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Book Cover
Author Verma, Brijesh, author

Title Roadside video data analysis : deep learning / Brijesh Verma, Ligang Zhang, David Stockwell
Published Singapore : Springer, 2017
Online access available from:
Springer eBooks    View Resource Record  


Description 1 online resource (xxv, 189 pages) : illustrations (some color)
Series Studies in computational intelligence, 1860-949X ; volume 711
Studies in computational intelligence ; v. 711. 1860-949X
Contents Chapter 1: Introduction -- Chapter 2: Roadside Video Data Analysis Framework -- Chapter 3: Non-Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 4: Deep Learning Techniques for Roadside Video Data Analysis -- Chapter 5: Case Study: Roadside Video Data Analysis for Fire Risk Assessment -- Chapter 6: Conclusion and Future Insight -- References
Summary This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment
Bibliography Includes bibliographical references
Notes Online resource; title from PDF title page (SpringerLink, viewed May 2, 2017)
Subject Data mining.
Digital video -- Data processing.
Machine learning.
Form Electronic book
Author Stockwell, David, author
Zhang, Ligang, author
ISBN 9789811045394 (electronic bk.)
9811045399 (electronic bk.)