Roadside Video Data Analysis Deep Learning
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...
Main Authors: | , , |
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Format: | eBook |
Language: | English |
Published: |
Singapore
Springer Nature Singapore
2017, 2017
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Edition: | 1st ed. 2017 |
Series: | Studies in Computational Intelligence
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
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 |
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Physical Description: | XXV, 189 p. 79 illus., 68 illus. in color online resource |
ISBN: | 9789811045394 |