Mar 30, 2020 · In this paper, we propose a deep learning approach for smartphone user identification based on analyzing motion signals recorded by the accelerometer and the ...
Dec 9, 2024 · In this paper, we propose a deep learning approach for smartphone user identification based on analyzing motion signals recorded by the ...
This paper transforms the discrete 3-axis signals from the motion sensors into a gray-scale image representation which is provided as input to a ...
Mar 23, 2020 · Abstract. In this paper, we propose a deep learning approach for smartphone user identification based on analyzing motion signals recorded ...
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Jan 6, 2022 · This paper shows the feasibility and effectiveness of using a compact 24 GHz Doppler radar with a built-in low-noise microwave amplifier (LNA) for detecting ...
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Jul 12, 2023 · This paper constructs a data set, improves the convolution neural network model, subsequently, new models are constructed through the neural network structure.
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Benegui and R. T. Ionescu, “Convolutional Neural Networks for User Identification based on Motion Sensors Represented as Images,” IEEE. Access, vol. 8, no. 1 ...
Applications using gesture-based human-computer interface require a new user login method with gestures because it does not have a traditional input method ...
Dec 19, 2023 · This paper provides a comprehensive study of the application of CNNs in the classification of HAR tasks.