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Brain-Computer Interfaces (BCIs) provide a way to communicate without movement and can offer significant clinical benefits. Electrical brain activity recorded using electroencephalography (EEG) can be automatically interpreted by supervised learning classifiers according to the descriptive features of the signal. This paper investigates the performance of novel feature extraction based on a signal...
Brain-Computer Interfaces (BCIs) provide a way to communicate without movement and can offer significant clinical benefits therefore. Electrical brain activity recorded using electroencephalography (EEG) can be automatically interpreted by supervised learning classifiers according to the descriptive features of the signal. Compressive sensing paradigm commonly used for array antenna design and signal...
Face recognition is a research hotspot in recent years. In order to improve recognition accuracy of face recognition, a feature selection method for face image based on Gabor feature and recursive feature elimination was proposed in this paper. Firstly, Gabor features were extracted from face image. Then, face image was divided into pieces and Gabor feature statistics of these pieces were linked in...
Automatic analysis of histopathological images has been widely investigated using computational image processing and machine learning techniques. Computer-aided diagnosis (CAD) systems and content-based image retrieval (CBIR) systems have been successfully developed for diagnosis, disease detection, and decision support in this area. In this paper, we focus on a scalable image retrieval method with...
Natural scene recognition and classification have received considerable attention in the computer vision community due to its challenging nature. Significant intra-class variations have largely limited the accuracy of scene categorization tasks: a holistic representation forces matching in strict spatial confinement; whereas a bag of features representation ignores the order or spatial layout of the...
Breast cancer is the most common malignant disease in women. Mammographic mass retrieval system can help radiologists to improve the diagnostic accuracy by retrieving biopsy-proven masses which are similar with the diagnostic ones. However, although screening mammograms usually consists of two-view(MLO and CC) mammography of the same breast, most breast CAD systems incorporate with image retrieval...
According to the symmetric characteristics of bispectrum, a novel feature extraction scheme, which includes the summation-at-every-column feature vector, the summation-at-every-row feature vector and their combination in a triangle area, one of the 12 symmetric areas of bispectrum, is proposed. By using One-against-One (OAO) method of multi classification of Support Vector Machine (SVM), the mean...
We propose a simple approach to fast extract the main text content from Web pages, especially online news pages. Most existing approaches need to construct the DOM tree structure from the HTML source of the Web page first, and then, extract the important content by pruning/merge the DOM branches/sub-trees. Such DOM tree processing tasks are very time-consuming. Our solution processes the HTML source...
The computational complexity of a texture classification algorithm is limited by the dimensionality of the feature space. A feature selection algorithm that can reduce the dimensionality of problem is often desirable, which has been studied by many authors because of its impact on the complexity of classifiers, Furthermore, feature selection in high dimension space is a NP hard problem. This paper...
In this paper, a new greedy feature selection algorithm is proposed to detect more precisely informative features. It overcomes the limitation of many existing MI-based gready feature selection algorithms. It is capable of detecting the relation of relevant feature combinations in some degree.In addition, the requirements of the memory storage and computation cost are low. Experimental results for...
Splog is the key challenge in the access of blogosphere. Existing splog-filtering methods are restricted to the way for traditional web spam filtering, without considering the characteristics of blogs. Inspired by the observation that fake writers (writers of splogs) have striking higher consistent writing behavior than real writers (writers of legitimate blogs), we propose to detect splogs by distinguishing...
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