Evaluating Techniques Based on Supervised Learning Methods in Casas Kyoto Dataset for Human Activity Recognition-Reference-Cited by-同舟云学术

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Evaluating Techniques Based on Supervised Learning Methods in Casas Kyoto Dataset for Human Activity Recognition

Published:2023 Issue: Volume: Page:253-269
ISSN:0302-9743
Container-title:Computer Information Systems and Industrial Management
language:
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Author:

García-Restrepo Johanna-Karinna,Ariza-Colpas Paola Patricia,Butt-Aziz Shariq,Piñeres-Melo Marlon Alberto,Naz Sumera,De-la-hoz-Franco Emiro

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-42823-4_19

Reference32 articles.

1. Welcome to CASAS. http://casas.wsu.edu/datasets/. Accessed 11 Sep 2022

2. Fettes, L., Bone, A.E., Etkind, S.N., Ashford, S., Higginson, I.J., Maddocks, M.: Disability in basic activities of daily living is associated with symptom burden in older people with advanced cancer or chronic obstructive pulmonary disease: a secondary data analysis. J. Pain Symptom Manage. 61(6), 1205–1214 (2021). https://doi.org/10.1016/J.JPAINSYMMAN.2020.10.012

3. Carlozzi, N.E., et al.: Daily variation in sleep quality is associated with health-related quality of life in people with spinal cord injury. Arch. Phys. Med. Rehabil. (2021). https://doi.org/10.1016/J.APMR.2021.07.803

4. Vich, G., Delclòs-Alió, X., Maciejewska, M., Marquet, O., Schipperijn, J., Miralles-Guasch, C.: Contribution of park visits to daily physical activity levels among older adults: evidence using GPS and accelerometer data. Urban Forestry Urban Green. 63, 127225 (2021). https://doi.org/10.1016/J.UFUG.2021.127225

5. Ariza-Colpas, P.P., et al.: Human activity recognition data analysis: History, evolutions, and new trends. Sensors 22(9), 3401 (2022)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sensors and Machine Learning Algorithms for Location and POSTURE Activity Recognition in Smart Environments;Automatic Control and Computer Sciences;2024-02

2. Human Activity Recognition Using Convolutional Neural Networks;Lecture Notes in Networks and Systems;2024

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