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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
Xile Gao1, Haiyong Luo2, Qu Wang3
1Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology Chinese Academy of Sciences, Beijing 100190, China. gaoxile17g@ict.ac.cn.
A new human activity recognition algorithm uses Stacking Denoising Autoencoder (SDAE) and LightGBM (LGB) for accurate sensor data analysis. This method achieves 95.99% accuracy, outperforming existing techniques in diverse scenarios.
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