Multimedia Data Learning

Zhongfei Mark Zhang () and Ruofei Bruce Zhang ()
Additional contact information
Zhongfei Mark Zhang: State University of New York, Binghamton University
Ruofei Bruce Zhang: Google

A chapter in Machine Learning for Data Science Handbook, 2023, pp 423-446 from Springer

Abstract: Abstract Multimedia data learning (a.k.a. multimedia data mining) is an emerging, multidisciplinary, and interdisciplinary research area with a wide spectrum of real-world applications related to a wide suite of areas noticeably including machine learning, artificial intelligence, data mining, multimedia, computer vision, and natural language processing. This chapter introduces important and fundamental concepts and theories of this area and provides further references.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-24628-9_19

Ordering information: This item can be ordered from
http://www.springer.com/9783031246289

DOI: 10.1007/978-3-031-24628-9_19

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().