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In this paper, an integrated emotion regulation system (IERS) is proposed based on the regulation process model for happiness improvement. Including extracting the valuable information from user's contents on social network, the IERS analyzes users' emotion variation and semanteme reflecting to the regulation process model and aim to appropriately feedback to users. The feedback sentences are chosen...
Low-level appearance as well as spatio-temporal features, appropriately quantized and aggregated into Bag-of-Words (BoW) descriptors, have been shown to be effective in many detection and recognition tasks. However, their effcacy for complex event recognition in unconstrained videos have not been systematically evaluated. In this paper, we use the NIST TRECVID Multimedia Event Detection (MED11 [1])...
Synthetic aperture radar (SAR) has become one of the most powerful observation tools in the studies of natural environments and Earth resources. However the granular appearance of speckle noise in synthetic aperture radar imagery makes it very difficult to visually and automatically interpret information of SAR data. In this paper, according to the inherent speckle property of SAR image, we proposed...
In this paper, we propose a max modular support vector machine (M2-SVM) and its two variations for pattern classification. The basic idea behind these methods is to decompose training samples of one class into several parts and learn each part by one modular classifier independently. To implement these methods, a dasiapart-against-otherspsila training strategy and a max modular combination principle...
This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported...
The traditional anti-spam techniques like black and white list can not meet the needs of the spam filter nowadays. Some machine learning techniques become very popular in the research of spam filter. Support vector machine is one of the most excellent methods in classifying. But these techniques are usually applied to spam identity based on the mail body textual content only, seldom discussing about...
Super-resolution image reconstruction has been one of the most active research areas in recent years. Based on the theory of statistical learning, Mercer condition and the wavelet frame, this paper proposes a new multiscale wavelet support vector regression model (MWSVR) to reconstruction super-resolution image from low-resolution image and missing data image. The SVM essence is kernel method and...
In this paper, we propose a robust method for the suppression of noise in medical ultrasound image by fusing the wavelet denoising technique with support vector regression (SVR). Based on the least squares support vector regression (LS- SVR), a new denoising operator and a new manipulation algorithm of wavelet coefficients are presented by incorporating neighboring coefficients. The proposed method...
In this paper, a new multiscale wavelet support vector machines model (MWSVM) is proposed, according to the Mercer condition, the wavelet frame theory and kernel function nature. From the statistical learning theory and the SVM model, pointed out the SVM essence is kernel method, the different kernel function has decided the different SVM. The choice of kernel parameters is simplified in MWSVM. By...
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