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Multiple view data with different feature representations have widely arisen in various practical applications. Due to the information diversity, fusing multiview features is very valuable for classification purpose. In this paper, we propose a new multifeature fusion method called fractional-order discriminative multiview correlation projection (FDMCP), which is based on fractional-order scatter...
Traditional recommendation only uses the single model of selection or rating to mining the users' interests. Network-Based Inference (NBI) is typical of selection single model. In order to make full use of information, in this paper, Recommendation based on bipartite network of two-step model(RBNTM) is put forward. The method on the basis of Network-based inference, considering scores also reflects...
Internet traffic classification is one of the key foundations for research works and traffic engineering in Internet. With the rapid increase of Internet applications and the number of Internet flow, the technique challenges are coupled with development of traffic classification all the time. Currently, the machine learning-based technique has attracted much attention, since it can address the issues...
Identification of constituent components of each sign gesture can be beneficial to the improved performance of sign language recognition (SLR), especially for large-vocabulary SLR systems. Aiming at developing such a system using portable accelerometer (ACC) and surface electromyographic (sEMG) sensors, we propose a framework for automatic Chinese SLR at the component level. In the proposed framework,...
Steady-state visual evoked potential (SSVEP) has been widely applied in brain computer interface (BCI) systems. The amplitude and phase features of SSVEP were commonly extracted by Fourier analysis method from single-channel EEG data. In the multichannel case, canonical correlation analysis (CCA) has been utilized for the analysis of frequency coding SSVEP. This paper presents the analysis of phase...
The structure in the multiple tables is so complex that we should not only improve the efficiency, but also insure the accuracy of classification when we classify the data. Some existing classification algorithms have good results in terms of the efficiency and the accuracy, for example: an efficient multi-relational Bayesian classifier based on the semantic relationship graph. But how to get the...
Text classification refers to determine the class of an unknown text according to its content in the given classification system. In order to extract fewer features to express the information in the text as much as possible, the paper analysis the various features' statistical properties and to extract the global features according to Zipf's law; and then, based on the statistical analysis of the...
An effective algorithm for number and letter character recognition is proposed in this paper. Our algorithm employs template matching, but it unlike traditional template matching method using the original pixel value to match. Our algorithm draws some features from the original image, and then obtains an eigenvector of 192 dimensions. Before drawing features, the image is disposed using math morphologic...
Currently, optical device, such as microscopes and CCD cameras, are utilized for identification of tool marks in the field of forensic science which mainly depend on the experience of forensic scientists. A new approach using extended fractal analysis technology to classify tool marks such as striation patterns is presented. it computes four directional multi-scale extended fractal parameters and...
Feature selection is a key problem to pattern recognition. So far, most methods of feature selection focus on sample data where class information is available. For sample data without class labels, however, the related methods for feature selection are few. This paper proposes a new way of unsupervised feature selection. Our method is a hybrid approach based on ranking the features according to their...
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