Overview
- Highlights deep learning, to better understand roadside video data segmentation
- Provides learning techniques based on concepts for roadside video data processing
- Discusses fire risk assessment based on roadside vegetation biomass estimation
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 711)
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Table of contents(6 chapters)
Keywords
- Feature extraction
- Classified roadside objects
- Roadside Fire Risk Assessment
- Neural Network Learning
- Support Vector Machine Learning
- K-Nearest Neighbor Learning
- Scene labeling
- Cluster Learning
- Vegetation biomass estimation
- Hierarchical Learning
- Fuzzy C-Means Learning
- Probabilistic Learning
- Ensemble Learning
About this book
Authors and Affiliations
-
School of Engineering and Technology, Central Queensland University, Brisbane, Australia
Brijesh Verma, Ligang Zhang, David Stockwell
About the authors
Brijesh Verma is a Professor and the Director of the Centre for Intelligent Systems at Central Queensland University, Brisbane, Australia. His main research interests include computational intelligence and pattern recognition. He has published a number of books and book chapters and over one hundred fifty papers in journals and conference proceedings.
He has served on the editorial boards of six international journals including Associate Editor for IEEE Transactions on Neural Networks and Learning Systems, Associate Editor for IEEE Transactions on Biomedicine in Information Technology and Editor-in-Chief for International Journal of Computational Intelligence & Applications. He has served on the organising and program committees of over thirty international conferences including IEEE International Joint Conference on Neural Networks (IJCNN) and IEEE Congress on Evolutionary Computation (CEC). He was the IJCNN Special Sessions Chair for 2012 IEEEWorld Congress on Computational Intelligence (WCCI). He was a Chair of a Special Session on Computational Intelligence based Ensemble Classifiers at IEEE IJCNN 2013 and a Chair of a Special Session on Machine Learning for Computer Vision at IEEE IJCNN 2014 and IEEE WCCI 2016. He is a Co-Chair of Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition at IEEE SSCI 2017.
He has served as the Chair of the IEEE Computational Intelligence Society’s Queensland Chapter in 2007-2008 and won the outstanding chapter award in 2009. He has also served on IEEE CIS senior members’ program subcommittee (2011-2012), IEEE CIS outstanding chapter award subcommittee (2009-2011) and IEEE CIS representative on IEEE Nanotechnology Council (2014-2015).
Ligang Zhang is a Research Fellow in the School of Engineering and Technology at Central Queensland University, Australia. His researchinterests include image segmentation and recognition, facial expression recognition, affective computing and machine learning. He has published more than 30 papers in journals and conference proceedings.
David Stockwell is an Adjunct Research Fellow at Central Queensland University and an Environmental Officer in the Queensland Department of Transport and Main Roads, Australia. He has a strong background in environmental data modelling and his research interests include statistical analysis, machine learning and pattern recognition. He has worked as a postdoctoral research fellow at the San Diego Supercomputer Center, University of California in USA. He has widely published and has over 4400 citations in Google scholar.
Bibliographic Information
Book Title: Roadside Video Data Analysis
Book Subtitle: Deep Learning
Authors: Brijesh Verma, Ligang Zhang, David Stockwell
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-981-10-4539-4
Publisher: Springer Singapore
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2017
Hardcover ISBN: 978-981-10-4538-7Published: 05 May 2017
Softcover ISBN: 978-981-13-5162-4Published: 12 December 2018
eBook ISBN: 978-981-10-4539-4Published: 28 April 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXV, 189
Number of Illustrations: 11 b/w illustrations, 68 illustrations in colour
Topics: Signal, Image and Speech Processing, Computational Intelligence, User Interfaces and Human Computer Interaction, Computer Imaging, Vision, Pattern Recognition and Graphics, Transportation Technology and Traffic Engineering