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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
This article is a correction to:
SemNet: Learning semantic attributes for human activity recognition with deep belief networks
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
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.”
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.
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, SwitzerlandCopyright © 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, b2xlLmoubWVuZ3Nob2VsQG50bnUubm8=
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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