Performance Boosting of Scale and Rotation Invariant Human Activity Recognition (HAR) with LSTM Networks Using Low Dimensional 3D Posture Data in Egocentric Coordinates
Human activity recognition (HAR) has been an active area in computer vision with a broad range of applications, such as education, security surveillance, and healthcare. HAR is a general time series classification problem. LSTMs are widely used for time series classification tasks. However, they wor...
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Format: | Article |
Language: | English |
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MDPI AG
2020-11-01
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Series: | Applied Sciences |
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Online Access: | https://www.mdpi.com/2076-3417/10/23/8474 |