CORRECTION article

Front. Big Data, 10 March 2023

Sec. Data Science

Volume 6 - 2023 | https://doi.org/10.3389/fdata.2023.1170820

Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks

  • 1. Department of ECE, Carnegie Mellon University, Pittsburgh, PA, United States

  • 2. Department of ECE, Anderson School of Management, University of California, Los Angeles, Los Angeles, CA, United States

  • 3. Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

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Incorrect Affiliation

In the published article, there was an error regarding the affiliation for Ole J. Mengshoel. Instead of being affiliated with “Department of ECE, Carnegie Mellon University, Pittsburgh, PA, United States”, they should be affiliated with “Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.”

Incorrect Correspondence

In the published article, there was an error in the correspondence. The correct corresponding author is “Ole J. Mengshoel” instead of “Harideep Nair.”

The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

human activity recognition, deep belief networks, semantic mid-level features, ubiquitous computing, multimodal sensing, artificial intelligence, internet of things

Citation

Venkatachalam S, Nair H, Zeng M, Tan CS, Mengshoel OJ and Shen JP (2023) Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks. Front. Big Data 6:1170820. doi: 10.3389/fdata.2023.1170820

Received

21 February 2023

Accepted

23 February 2023

Published

10 March 2023

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

6 - 2023

Updates

Copyright

*Correspondence: Ole J. Mengshoel

This article was submitted to Data Science, a section of the journal Frontiers in Big Data

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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