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Roadside Video Data Analysis - Deep Learning (Paperback, Softcover reprint of the original 1st ed. 2017) Loot Price: R3,353
Discovery Miles 33 530
Repayment Terms: R314 pm x 12*
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Roadside Video Data Analysis - Deep Learning (Paperback, Softcover reprint of the original 1st ed. 2017): Brijesh Verma, Ligang...

Roadside Video Data Analysis - Deep Learning (Paperback, Softcover reprint of the original 1st ed. 2017)

Brijesh Verma, Ligang Zhang, David Stockwell

Series: Studies in Computational Intelligence, 711

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Loot Price R3,353 Discovery Miles 33 530 | Repayment Terms: R314 pm x 12*

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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.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: Studies in Computational Intelligence, 711
Release date: December 2018
First published: 2017
Authors: Brijesh Verma • Ligang Zhang • David Stockwell
Dimensions: 235 x 155mm (L x W)
Format: Paperback
Pages: 189
Edition: Softcover reprint of the original 1st ed. 2017
ISBN-13: 978-981-13-5162-4
Categories: Books > Professional & Technical > Civil engineering, surveying & building > Highway & traffic engineering
Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
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LSN: 981-13-5162-7
Barcode: 9789811351624

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