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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

This article is a correction to:

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

    1. Read original article
\nShanmuga VenkatachalamShanmuga Venkatachalam1Harideep NairHarideep Nair1Ming ZengMing Zeng1Cathy Shunwen TanCathy Shunwen Tan2Ole J. Mengshoel Ole J. Mengshoel3*John Paul ShenJohn Paul Shen1
  • 1Department of ECE, Carnegie Mellon University, Pittsburgh, PA, United States
  • 2Department of ECE, Anderson School of Management, University of California, Los Angeles, Los Angeles, CA, United States
  • 3Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

A corrigendum on
SemNet: Learning semantic attributes for human activity recognition with deep belief networks

by Venkatachalam, S., Nair, H., Zeng, M., Tan, C. S., Mengshoel, O. J., and Shen, J. P. (2022). Front. Big Data 5:879389. doi: 10.3389/fdata.2022.879389

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.

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.

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

Copyright © 2023 Venkatachalam, Nair, Zeng, Tan, Mengshoel and Shen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ole J. Mengshoel, b2xlLmoubWVuZ3Nob2VsJiN4MDAwNDA7bnRudS5ubw==

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.