ByteTrack: a deep learning approach for bite count and bite rate detection using meal videos in children

Authors

Kathleen Keller (ORCID: https://orcid.org/0000-0001-6481-7018)
Yashaswini R. Bhat (ORCID: https://orcid.org/0000-0002-0465-1797)
Timothy R. Brick (ORCID: https://orcid.org/0000-0002-3339-9279)
Alaina L. Pearce (ORCID: https://orcid.org/0000-0003-3157-6566)

Institutions

Pennsylvania State University (US)

Publication Details

Journal: Frontiers in Nutrition
Published: 2025-10-03
DOI: https://doi.org/10.3389/fnut.2025.1610363
Primary Topic: IoT-based Smart Home Systems
Type: article
Field-Weighted Citation Impact: 0.00

Funders

U.S. Department of Agriculture
Pennsylvania State University
National Institutes of Health
Institute for Computational and Data Sciences, Pennsylvania State University
National Center for Advancing Translational Sciences

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article

ByteTrack: a deep learning approach for bite count and bite rate detection using meal videos in children

Kathleen Keller, Yashaswini R. Bhat, Timothy R. Brick, Alaina L. Pearce

Oct 3, 2025

Frontiers in Nutrition

IoT-based Smart Home Systems

article

ByteTrack: a deep learning approach for bite count and bite rate detection using meal videos in children

Kathleen Keller, Yashaswini R. Bhat, Timothy R. Brick, Alaina L. Pearce

October 3, 2025article en

Abstract

No abstract available for this paper.

Frontiers in NutritionVol. 12

Pennsylvania State University (US)

U.S. Department of Agriculture, Pennsylvania State University, National Institutes of Health, Institute for Computational and Data Sciences, Pennsylvania State University, National Center for Advancing Translational Sciences

Openalex Percentile: Top 73%

IoT-based Smart Home Systems

DOI Open Access PDF OpenAlex

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