RMPCT-Net: a multi-channel parallel CNN and transformer network model applied to HAR using FMCW radar-Reference-Cited by-同舟云学术

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RMPCT-Net: a multi-channel parallel CNN and transformer network model applied to HAR using FMCW radar

Published:2023-12-26 Issue: Volume: Page:
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Gu Minming,Chen Zhixiang,Chen Kaiyu,Pan Haipeng

Funder

Zhejiang Province's R&D research and development projects

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-023-02894-4.pdf

Reference37 articles.

1. Dang, J., Min, K., Wang, H., Piran, M., Lee, C., Moon, H.: Sensor-based and vision-based human activity recognition: a comprehensive survey. Pattern Recogn. 108, 107561 (2020)

2. Park, S., Park, J., Al-masni, M., Al-antari, M., Uddin, M., Kim, T.: A depth camera-based human activity recognition via deep learning recurrent neural network for health and social care services. Procedia Comput. Sci. 100, 78–84 (2016)

3. Lu X., Wang L., Tian Y., Hu J., Pan Y., Zhang E., Zhang Y.: Towards WiFi-based real-time sensing model deployed on low-power devices. In: IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS). pp. 385–393 (2022)

4. Jalal A., Mahmood M., Hasan A.: Multi-features descriptors for human activity tracking and recognition in Indoor-outdoor environments. In: 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST). pp. 371–376 (2019)

5. Ohashi T., Ikegami Y., Yamamoto K., Takano W., Nakamura Y.: Video motion capture from the part confidence maps of multi-camera images by spatiotemporal filtering using the human skeletal model. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 4226–4231 (2018)

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