Multimodal Scene Understanding: Algorithms, Applications and Deep Learning
Language: English
Published by Elsevier Science Publishing Co Inc, 2019
- Softcover
- New
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Seller Inventory # B9780128173589
- Title
- Multimodal Scene Understanding: Algorithms, Applications and Deep Learning
- Author
- Michael Ying Yang
- Publisher
- Elsevier Science Publishing Co Inc
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback / softback
- Language
- English
- ISBN 10
- 0128173580
- ISBN 13
- 9780128173589
- Item weight
- 641 grams
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms.
Researchers collecting and analyzing multi-sensory data collections - for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful.
"Synopsis" may belong to another edition of this title.
About the Author
His works received several awards, including a DAGM-Prize 2002 , Dr.-Ing. Siegfried Werth Prize 2003, DAGM-Main Prize 2005, IVCNZ best student paper award , DAGM-Main Prize 2007, Olympus-Prize 2007, ICPRAM Best student paper award 2014, ICMC Best student paper award 2014, the WACV 2015 Challenge Award, the Günter Enderle Award (Eurographics) 2017 and the CVPR 2017 Multi-Object Tracking Challenge. In 2011, the European Commission awarded Bodo Rosenhahn with a 1.43 million Euros ERC-Starting Grant and in 2013 with a POC Grant. He published more than 180 research papers, journal articles and book chapters, holds more than 10 patents and edited several books.
Full professor at the University of Verona, Italy, and director of the PAVIS (Pattern Analysis and Computer Vision) department at the Istituto Italiano di Tecnologia. He took the Laurea degree in Electronic Engineering in 1989 and a Ph.D. in Electronic Engineering and Computer Science in 1993 at the University of Genova, Italy.
His main research interests include: computer vision and pattern recognition/machine learning, in particular, probabilistic techniques for image and video processing, with applications on video surveillance, biomedical image analysis and bioinformatics.
"About the title" may belong to another edition of this title.
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