Enhancing human activity recognition using features reduction in IoT edge and Azure cloud

Author:

Wazwaz Ayman A.ORCID,Amin Khalid M.,Semari Noura A.,Ghanem Tamer F.

Publisher

Elsevier BV

Subject

Modeling and Simulation,Applied Mathematics,Analysis,General Decision Sciences

Reference45 articles.

1. Task offloading in edge computing for machine learning-based smart healthcare;Aazam;Comput. Netw.,2021

2. Edge-cloud computing for internet of things data analytics: Embedding intelligence in the edge with deep learning;Ghosh;IEEE Trans. Ind. Inform.,2021

3. V. Sze, Y.-H. Chen, J. Emer, A. Suleiman, Z. Zhang, Hardware for machine learning: Challenges and opportunities, in: 2018 IEEE Custom Integrated Circuits Conference, CICC, 2018, pp. 1–8, http://dx.doi.org/10.1109/CICC.2018.8357072.

4. A deep learning-based model for human activity recognition using biosensors embedded into a smart knee bandage;Mekruksavanich;Procedia Comput. Sci.,2022

5. TransTM: A device-free method based on time-streaming multiscale transformer for human activity recognition;Liu;Def. Technol.,2023

Cited by 1 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. Deep Residual Neural Network for Aggressive Physical Activity Recognition Using Surface Electromyography Sensors;2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS);2023-10-17

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