Computer Vision-Based Human Activity Detection for Intensive Care Patients: A Case Study Based on Region of Interest (ROI)
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-60140-8_8
Reference34 articles.
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4. Jalal, A., Kamal, S., & Kim, D. (2017). A depth video-based human detection and activity recognition using multifeatures and embedded hidden Markov models for health care monitoring systems. International Journal of Interactive Multimedia and Artificial Intelligence, 4(4), 54. https://doi.org/10.9781/ijimai.2017.447
5. Capela, N., Lemaire, E., & Baddour, N. (2015). Feature selection for wearable smartphone-based human activity recognition with able-bodied, elderly, and stroke patients. PLoS One, 10(4), e0124414. https://doi.org/10.1371/journal.pone.0124414
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