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Activity sensing has become a key technology for many ubiquitous applications, such as exercise monitoring and elder care. Most traditional approaches track the human motions and perform activity recognition based on the waveform matching schemes in the raw data representation level. In regard to the complex activities with relatively large moving range, they usually fail to accurately recognize these...
In this paper, we propose a new approach for the person re-identification problem, discovering the correct matches for a query pedestrian image from a set of gallery images. It is well motivated by our observation that the overall complex inter-camera transformation, caused by the change of camera viewpoints, person poses and view illuminations, can be effectively modelled by a combination of many...
In this paper, a novel method based on Hilbert-Huang Transform (HHT) and backpropagation (BP) neural network is proposed to perform automatic sleep stages classification. Features extracted from 30-second epoch of EEG using HHT are good representations of EEG signal. A three-layer BP neural network is employed to classify these features to one appropriate stage. For a four-stage classification, consisting...
Infrasound is ideally suited to provide essential information of these earthquakes without any invasive measures. This necessitates automatic processing of the data as the captured phenomena need to be sortedbefore further analysis can be undertaken. Extracting the physical characters of different signals by signal processing such as Fourier Transform and Wavelets Transform are generally employed...
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