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These experiments were conducted using ten people who were all fresh participants (i.e., who had not participated in the training dataset collection). The proposed wink-gesture classifier achieved 95.4% average accuracy, with the worst case of entropy of 0.24, in regard to the ten participants ...
This research was also supported by a Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korean government (MOTIE) (20214000000090, Fostering Human Resources Training in Advanced Hydrogen Energy Industry). Data Availability Statement: The data presented in this ...
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A type of device calibration-free method, which does not need to collect training data for device calibration, utilises the RSS difference between APs or locations to mitigate the effect of using heterogeneous smartphones. Shu et al. [38] proposed a gradient fingerprinting method, which leveraged...