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Human Activity Recognition: A review
2022 10th International Symposium on Digital Forensics and Security (ISDFS), 2022João Gonçalo Pereira +1 more
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Human Activity Recognition based on WaveNet
2021 IEEE 7th World Forum on Internet of Things (WF-IoT), 2021This paper makes a comprehensive study on human activity recognition based on CNN and RNN and proposes an alternative way to solve HAR based on WaveNet. The model is full probability autoregressive and can be used as a discriminant model. Therefore, this paper attempts to use WaveNet to solve HAR. By comparing the results of CNN, RNN and WaveNet models
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Active classification for human action recognition
2013 IEEE International Conference on Image Processing, 2013In this paper, we propose a novel classification method involving two processing steps. Given a test sample, the training data residing to its neighborhood are determined. Classification is performed by a Single-hidden Layer Feedforward Neural network exploiting labeling information of the training data appearing in the test sample neighborhood and ...
Alexandros Iosifidis +2 more
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Human Activity Recognition Based on Similarity
2014 IEEE 17th International Conference on Computational Science and Engineering, 2014Human activity recognition based on smart phones has been widely used in many fields including the mobile context awareness and inertial positioning. Compared to the activity recognition whose sensor location is fixed, the activity recognition based on smartphones has a new problem because the mobile direction and position are not fixed. In this paper,
Yangda Zhu +3 more
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1997
A fundamental goal of work in recognition is to discover easily-computed visual features which are efficient indices of members of the class which is to be recognized. The hypothesis behind work in motion-based recognition is that features describing motion in the input can be efficient indices for large classes of objects and activities of interest to
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A fundamental goal of work in recognition is to discover easily-computed visual features which are efficient indices of members of the class which is to be recognized. The hypothesis behind work in motion-based recognition is that features describing motion in the input can be efficient indices for large classes of objects and activities of interest to
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Special section on human activity recognition
Pervasive and Mobile Computing, 2012[No abstract available]
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Human Activity Recognition with Wearable Sensors
2008This thesis investigates the use of wearable sensors to recognize human activity. The activity of the user is one example of context information -- others include the user's location or the state of his environment -- which can help computer applications to adapt to the user depending on the situation.
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Imaging and fusing time series for wearable sensor-based human activity recognition
Information Fusion, 2020Zhiguang Qin +2 more
exaly

