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Web text classification is the process of determine the text types automatically under a given classification, according to the text content. Web text categorization system is the use of machine learning, knowledge engineering and other related fields of knowledge, access to the web on the text, after text preprocessing, Chinese word segmentation and training classifier, using classification algorithm...
Texture segmentation by Pseudo Jacobi -Fourier moments is presented in this paper. Given a window size, moments for each pixel in the image are computed within small local windows, and then texture feature images be obtained by using a nonlinear transducer. Finally, each pixel in the image is classified by K-mean clustering algorithm.
Emotional state recognition is an important component for efficient human-computer interaction. Most existing works address this problem using 2D features, but they are sensitive to head pose, clutter, and variations in lighting conditions. The general 3D based methods only consider geometric information for feature extraction. In this paper, we present a real 3D visual features based method for human...
In this paper, we further develop the idea of subject specific mental tasks selection process as a necessary prerequisite in any EEG-based brain computer interface (BCI) application. While, in two previous researches we proved - using the EEG-extracted auto-regressive (AR) parameters and twelve different mental tasks -, the major gains one can obtain in tasks classification performance only by selecting...
Cognitive radio (CR) is a promising technology for improving the utilization of the scarce radio spectrum by allowing secondary users to regularly sense the spectrum and opportunistically access the under-utilized frequency bands. However, spectrum sensing in CR environment is a challenging task due to varying radio channel conditions and might lead to interference with licensed users. In this paper,...
We propose an automatic moment-based image recognition technique in this paper. The problem to be solved consists of classifying the images from a set, using the content similarity. In the feature extraction stage, we compute a set of feature vectors using area moments. An automatic unsupervised feature vector classification approach is proposed next. It uses a hierarchical agglomerative clustering...
This paper presents the performance of support vector machine to classify the multi-class arrhythmia dataset by pre-selecting sets of feature that best suit the training data set in two-class fashion. By allowing freedom of feature dimension selection in different grouping in classification procedure, the classification performance is comparable to one that uses constant feature dimension but with...
Making the semantic description and automatic semantic annotation of the image which contains rich contents and intuitive expression is a research subject that is challenging. It is a key technology of realizing fast and effective image retrieval and a research focusing on cross media mining. Also it has great application value in various kinds of fields. This paper studies and discusses image media...
This paper presents a novel technique for power quality disturbance classification. Wavelet transform (WT) has been used to extract some useful features of the power system disturbance signal and discrete harmony search with modified differential mutation operator (DHS_MD) have been used for feature dimension reduction in order to achieve high classification accuracy. Next, a probabilistic neural...
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
This paper presents a method for recognizing Bengali printed characters by using view-based and layer-based approaches. Two different view-based approaches, the top-bottom and the left-right have been used. The layer-based approach is also considered here. No thinning or segmentation is required. The individual character is taken as a whole image. The characteristic points are extracted from the views...
Under the framework of PU(Positive data and Unlabeled data), this paper originally proposes a three-setp algorithm. First, CoTraining is employed for filtering out the likely positive data from the unlabeled dataset U. Second, affinity propagation (AP) approach attempts to pick out the strong positive from likely positive set which is produced in first step. Those data picked out can be supplied to...
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