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Multimodal Analytics for Next-Generation Big Data Technologies and Applications
Details
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.
Explains multimodality data analytics in big data environments Important techniques applied to image and speech processing, multimodal information processing, data science, and artificial intelligence Valuable for researchers, professionals and students in engineering, and computer science
Inhalt
Foundations and Principles.- Advanced Information and Knowledge Processing.- Advanced Models and Architectures.- Advanced Applications and Future Trends.<p
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783319975979
- Auflage 1st edition 2019
- Editor Kah Phooi Seng, Junbin Gao, Alan Wee-Chung Liew, Li-Minn Ang
- Sprache Englisch
- Genre Anwendungs-Software
- Größe H241mm x B160mm x T28mm
- Jahr 2019
- EAN 9783319975979
- Format Fester Einband
- ISBN 3319975978
- Veröffentlichung 30.07.2019
- Titel Multimodal Analytics for Next-Generation Big Data Technologies and Applications
- Gewicht 776g
- Herausgeber Springer International Publishing
- Anzahl Seiten 408
- Lesemotiv Verstehen