B.Tech. (Electronics and Computer Engineering), Department of Electronics Technology, Guru Nanak Dev University, Amritsar
JournalPIJST
Volume / Issue1 / 6
Pages16–23
Published30 Jun 2024
Paper IDPIJST16J24003
Views / Downloads1 / 0
Article summary
Abstract
: Human activity recognition (HAR) aims to enable computers to understand various human activities, such as walking, running, or dancing, by analyzing movement patterns. This technology has significant applications in fields like healthcare for monitoring elderly individuals and sports for tracking performance. Traditional HAR methods often struggle with complex and variable movements or large datasets. This paper explores the potential of deep learning to overcome these challenges by using neural networks that learn from examples and identify intricate patterns in data. Specifically, we investigate how convolutional neural networks (CNNs) and recurrent neural networks (RNNs) can process data from movement sensors to accurately recognize human activities. We also address the challenges of preparing data for analysis, selecting appropriate network architectures, and interpreting the results. This study highlights the transformative potential of deep learning in HAR, aiming to enhance the understanding of human movements and foster innovative applications across various domains.
Citation record
How to cite this article
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh (2024). Deep Learning for Human Activity Recognition Tasks. Procedure International Journal of Science and Technology, 1(6), 16–23. https://doi.org/10.62796/pijst.2024v1i603
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh. “Deep Learning for Human Activity Recognition Tasks.” Procedure International Journal of Science and Technology, vol. 1, no. 6, 2024, pp. 16–23. https://doi.org/10.62796/pijst.2024v1i603
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh. “Deep Learning for Human Activity Recognition Tasks.” Procedure International Journal of Science and Technology 1, no. 6 (2024): 16–23. https://doi.org/10.62796/pijst.2024v1i603
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh (2024) ‘Deep Learning for Human Activity Recognition Tasks’, Procedure International Journal of Science and Technology, 1(6), pp. 16–23. Available at: https://doi.org/10.62796/pijst.2024v1i603.
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh, “Deep Learning for Human Activity Recognition Tasks,” Procedure International Journal of Science and Technology, vol. 1, no. 6, pp. 16–23, 2024. https://doi.org/10.62796/pijst.2024v1i603.
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh. Deep Learning for Human Activity Recognition Tasks. Procedure International Journal of Science and Technology. 2024;1(6):16–23. https://doi.org/10.62796/pijst.2024v1i603.
Rajdeep Singh Sohal, Karunjot Singh, Mohabat Pal Singh. Deep Learning for Human Activity Recognition Tasks. Procedure International Journal of Science and Technology 2024, 1 (6), 16–23. https://doi.org/10.62796/pijst.2024v1i603.
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