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- W4321608858 abstract "Human activity recognition (HAR) is the method to identify an activity of a human by rendering images, video, and sensor data collectively. While performing HAR and working with images, the video dataset is not secure because these datasets reveal the user identity, but the sensor data do not. Therefore, in this paper, we proposed a cost-efficient deep neural network model i.e. light human activity recognition system (LightHARs) which takes less parameters and computational time as compared to existing HAR models. It outperformed existing models by achieving 4.5% more accuracy." @default.
- W4321608858 created "2023-02-24" @default.
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- W4321608858 date "2023-01-01" @default.
- W4321608858 modified "2023-09-27" @default.
- W4321608858 title "LightHARs: A Light Human Activity Recognition System" @default.
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- W4321608858 doi "https://doi.org/10.1007/978-981-19-6088-8_39" @default.
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