Joint recognition for location and activity based on multidimensional features of CSI images
Author:
Funder
National Natural Science Foundation of China
Applied Basic Research Program Project of Liaoning Province
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13042-024-02266-5.pdf
Reference35 articles.
1. Gao C, Chen Y, Jiang X et al (2023) Bi-STAN: bilinear spatial-temporal attention network for wearable human activity recognition. Int J Mach Learn Cyber 14: 2545–2561. https://doi.org/10.1007/s13042-023-01781-1
2. Cui W, Li B, Zhang L, et al (2021) Device-free single-user activity recognition using diversified deep ensemble learning. Appl Soft Comput 102:107066. https://doi.org/10.1016/j.asoc.2020.107066
3. Xu L, Lan C, Zeng W et al (2022) Skeleton-based mutually assisted interacted object localization and human action recognition. IEEE Trans Multimedia 25: 4415–4425. https://doi.org/10.1109/TMM.2022.3175374
4. Lawal IA, Bano S (2020) Deep human activity recognition with localisation of wearable sensors. IEEE Access 8:155060-155070. https://doi.org/10.1109/ACCESS.2020.3017681
5. Tian Y, Chen C, Zhang Q et al (2023) Multidimensional information recognition algorithm based on CSI decomposition. IEEE Internet Things J 10(10): 9234–9248. https://doi.org/10.1109/JIOT.2023.3234054
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