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Due to the influence of indoor signal multipath effect and human disturbance, the indoor positioning technology of WiFi fingerprint based on deep learning is poor stability. The large sample and accurate data in the room is very difficult to collect for weights training of deep learning, so it is difficult to be widely used. Firstly, the innovative algorithm with multi-sensor fingerprint and deep...
Long Short-Term Memory (LSTM) is the primary recurrent neural networks architecture for acoustic modeling in automatic speech recognition systems. Residual learning is an efficient method to help neural networks converge easier and faster. In this paper, we propose several types of residual LSTM methods for our acoustic modeling. Our experiments indicate that, compared with classic LSTM, our architecture...
This paper addresses the problem of human activity recognition based on wearable sensors. In resent years researches on human daily activity recognition have enabled impressive result on substantial amount of labeled training samples. However, unlabeled samples are readily available but labeled ones are often difficult and slow to obtain. In order to reduce the level of supervision, this paper analyzes...
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