Evaluate action primitives for human activity recognition using unsupervised learning approach
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8354335/8356324/08356374.pdf?arnumber=8356374
Cited by 12 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. Human Activity Recognition Based on On-Body Antennas and Semi-Supervised Learning;2023 17th European Conference on Antennas and Propagation (EuCAP);2023-03-26
2. Evaluating Techniques Based on Supervised Learning Methods in Casas Kyoto Dataset for Human Activity Recognition;Computer Information Systems and Industrial Management;2023
3. A survey on unsupervised learning for wearable sensor-based activity recognition;Applied Soft Computing;2022-09
4. An Integration of feature extraction and Guided Regularized Random Forest feature selection for Smartphone based Human Activity Recognition;Journal of Network and Computer Applications;2022-08
5. ConvAE-LSTM: Convolutional Autoencoder Long Short-Term Memory Network for Smartphone-Based Human Activity Recognition;IEEE Access;2022
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