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Researchers have done extensive work on establishing an accurate user profile, which has been verified an effective way to implement the user marketing accurately and effectively. In this paper, we will present a feature extraction method based on the fusion of Word2Vec and TF-IDF, and try to establish a user profile. The vector space model (VSM) contains the word vector calculated by Word2Vec, and...
Automatic respiratory sound (RS) analysis provides a possible solution for the minimization of inherent subjectivity caused by auscultation via stethoscope, and it allows a reproducible quantification of RS. As one of the crucial initial steps, reliable unsupervised respiratory phase detection plays an important role in automatic RS analysis. In this paper, a novel unsupervised phase detection scheme...
Camera calibration is a fundamental problem in computer vision community. Already extensive research has been conducted and emerge a large number of excellent calibration algorithm, but there is few studies of automatic calibration system, the camera calibration toolbox for the moment almost use multi-use manual or semi-automatic marking the target area and extracting feature points, inefficient and...
The stability of the output image sequences is vital for camera system. In order to stabilize video image sequences, a new digital image stabilization system with motion estimation based on binocular ranging and sensor is proposed. According to the imaging model of camera, the estimation of image motion vector is based on the distance of objects and the attitude information of camera. Binocular vision...
Computerized patient monitoring provides valuable information on clinical disorders in medical practice, and it triggers the need to simplify the extent of resources required to describe large set of complex biomedical signals. In this paper, we present a new signal quantification method based on block-wise similarity measurement between the neighboring regions in the optimized log-frequency spectrogram...
Sparse approximation is a novel technique in applications of event detection problems to long-term complex biomedical signals. It involves simplifying the extent of resources required to describe a large set of data sufficiently for classification. In this paper, we propose a multivariate statistical approach using dynamic principal component analysis along with the non-overlapping moving window technique...
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