Roadside Video Data Analysis: Deep Learning (Studies in Computational Intelligence Book 711) 1st ed. 2017 Edition, Kindle Edition

Book 189 of 367: Studies in Computational Intelligence
Flip to back Flip to front
Audible Sample Playing... Paused   You are listening to a sample of the Audible narration for this Kindle book.
Learn more
ISBN-13: 978-9811045387
ISBN-10: 9811045380
Why is ISBN important?
This bar-code number lets you verify that you're getting exactly the right version or edition of a book. The 13-digit and 10-digit formats both work.
Scan an ISBN with your phone
Use the Amazon App to scan ISBNs and compare prices.
Kindle App Ad
Loading your book clubs
There was a problem loading your book clubs. Please try again.
Not in a club? Learn more
Amazon book clubs early access

Join or create book clubs

Choose books together

Track your books
Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club that’s right for you for free.
Digital List Price: $139.00

Deliver to your Kindle or other device

Buy for others

Give as a gift or purchase for a team or group.Learn more

Buying and sending eBooks to others

Select quantity
Buy and send eBooks
Recipients can read on any device

Additional gift options are available when buying one eBook at a time.  Learn more

These ebooks can only be redeemed by recipients in the US. Redemption links and eBooks cannot be resold.


Today through selected date:

Rental price is determined by end date.

Deliver to your Kindle or other device

The Amazon Book Review
The Amazon Book Review
Book recommendations, author interviews, editors' picks, and more. Read it now.
click to open popover

Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.

  • Apple
  • Android
  • Windows Phone
    Windows Phone
  • Click here to download from Amazon appstore

To get the free app, enter your mobile phone number.

Amazon Business : For business-only pricing, quantity discounts and FREE Shipping. Register a free business account

Editorial Reviews

From the Back Cover

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. --This text refers to the hardcover edition.

About the Author

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 IEEE World 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 research interests 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.

--This text refers to the hardcover edition.

Product details

  • File Size : 11756 KB
  • Publication Date : April 28, 2017
  • Word Wise : Not Enabled
  • ASIN : B071YQRM2X
  • Print Length : 214 pages
  • Publisher : Springer; 1st ed. 2017 Edition (April 28, 2017)
  • Language: : English
  • Text-to-Speech : Enabled
  • Enhanced Typesetting : Enabled
  • X-Ray : Not Enabled
  • Lending : Not Enabled