Multimodal Analytics for Next-Generation Big Data Technologies and Applications Hardcover - 2019
by Kah Phooi Seng (Editor); Li-Minn Ang (Editor); Alan Wee-Chung Liew (Editor)
From the rear cover
This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications.
The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.
Details
- Title Multimodal Analytics for Next-Generation Big Data Technologies and Applications
- Author Kah Phooi Seng (Editor); Li-Minn Ang (Editor); Alan Wee-Chung Liew (Editor)
- Binding Hardcover
- Pages 391
- Volumes 1
- Language ENG
- Publisher Springer
- Date 2019-07-30
- Illustrated Yes
- Features Illustrated
- ISBN 9783319975979 / 3319975978
- Weight 1.64 lbs (0.74 kg)
- Dimensions 9.21 x 6.14 x 0.94 in (23.39 x 15.60 x 2.39 cm)
- Dewey Decimal Code 006.3
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Multimodal Analytics for Next-Generation Big Data Technologies and Applications
by Kah Phooi Seng (Editor), Li-minn Ang (Editor), Alan Wee-Chung Liew (Editor), Junbin Gao (Editor)
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Multimodal Analytics for Next-generation Big Data Technologies and Applications
by Seng, Kah Phooi (Editor)/ Ang, Li-minn (Editor)/ Liew, Alan Wee-chung (Editor)/ Gao, Junbin (Editor)
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