Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

Title
Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines
Authors
Keywords
-
Journal
Information Fusion
Volume 54, Issue -, Pages 44-60
Publisher
Elsevier BV
Online
2019-07-18
DOI
10.1016/j.inffus.2019.07.004

Ask authors/readers for more resources

Find Funding. Review Successful Grants.

Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.

Explore

Publish scientific posters with Peeref

Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.

Learn More