deep learning (DL)
This dataset contains electrical measurements collected in the context of the paper "An Embedded Deep Learning NILM System: A Year-long Field Study in Real Houses".
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Current radar fall detection techniques based on deep learning (DL) networks are often too complex for real-time detection. This paper proposes a real-time fall detection approach by reducing the complexity of the DL networks and the UWB radar hardware requirements. A multi-indoor scene behaviour dataset of 40 subjects is established using K-band UWB radar. A sliding window-based dataflow augmentation method is proposed to augment and balance the given datasets.
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