The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Developing 3D palmprint recognition systems has recently begun to draw attention of researchers. Compared with its 2D counterpart, 3D palmprint has several unique merits. However, most of the existing 3D palmprint matching methods are designed for one-to-one verification and they are not efficient to cope with the one-to-many identification case. In this paper, we fill this gap by proposing a collaborative...
Hyperspectral face images present productive information captured using a Hyperspectral camera compared to normal RGB camera capturing face images. Hyper spectral imaging is the collecting and processing of information from across the visible electromagnetic spectrum. Hyper spectral imaging deals with the imaging of narrow spectral bands over a continuous visible spectral range, and produces the spectra...
The word-to-vector (W2V) technique represents words as low-dimensional continuous vectors in such a way that semantic related words are close to each other. This produces a semantic space where a word or a word collection (e.g., a document) can be well represented, and thus lends itself to a multitude of applications including document classification. Our previous study demonstrated that representations...
In the aging society such as Japan, it is very important to improve the quality of nursing-care for keeping our quality of life. Our final goal is to develop a computer aided evaluation system to improve the quality of nursing-care. For evaluating the quality of actual nursing, we have been collecting texts that are written by nurses using our Web based system. In our previous works, a SVM based classification...
Classification of malicious code by machine learning gives more flexible and adaptable prediction result than by existing approaches [1]. But the approach just can identify looks-like malicious code instead of real malicious one. In this research, a novel method to reduce the vagueness in the classification by machine learning to consider code sequence.
Effective motor imagery (MI) classification based on electroencephalogram (EEG) signals for Brain Computer Interface (BCI) is an active area of research. Classification is largely dependent on the feature vector and the type of classifier. This paper reports a study on the use of bispectrum for classifying left and right hand MI based on surface EEG from electrode positions C3 and C4. EEG signals...
This study proposes a Principal Component Analysis (PCA) method to analyze motor's current waveforms for determining the motor's quality types. The proposed method which consists of data training algorithm and motor's quality types decision algorithm. In the data training algorithm, the input signals are selected from the sample motors with known motor's quality type. It carries out three major processing...
In order to solve the problems of traditional machine learning methods for automatic classification of vulnerability, this paper presents a novel machine learning method based on LDA model and SVM. Firstly, word location information is introduced into LDA model called WL-LDA (Weighted Location LDA), which could acquire better effect through generating vector space on themes other than on words. Secondly,...
This paper presents a method of modern deep machine learning and its application in dimension reduction and lossy compression. Deep belief networks (or DBN's), first proposed by Yoshua Bengio, are hierarchic, stochastic, neural networks with appropriate architecture and dedicated training algorithms. They are composed of layers, each one of which is a restricted Boltzmann machine (or RBM). There exists...
Emergence of Web 2.0, internet users can share their contents with other users using social networks. In this paper microbloggers' contents are evaluated with respect to how they reflect their categories. Migrobloggers' category information, which is one of the four categories that are economy sport, entertainment or technology, is taken from wefollow.com application. 2105 RSS news feeds, whose category...
Reject inference is a term that distinguishes attempts to correct models in view of the characteristics of rejected applicants. The main difficulty in establishing reject inference model is that the ¡®through-the-door' applicant population is unavailable. In this paper, we propose a hybrid data mining technique for reject inference. It is a three-stage approach: k-means cluster, support vector machines...
Web contents are going overwhelming today. The numerous online documents, webpages, e-books, etc. are much useful but obtaining them is also time-consuming. Text categorization is one of the solutions to the issue. For all text categorization method, Support Vector Machines (SVM) is one of the most acceptable one. However, to perform more efficiently on webpages, it is necessary to add improvements...
A medical staff needs to check sputum accumulation in patient's respiratory tract by lung sounds auscultation at any time, and it is the big burden for the staff. This paper aims to develop a system which notifies appropriate timing for the tracheal suction for the medical staff by analyzing lung sounds of the patients. We present a novel framework about automatic sputum detection from lung sounds...
The purpose of a focused crawler is to crawl more topical portions of the Internet precisely. How to predict the visit priorities of candidate URLs whose corresponding pages have yet to be fetched is the determining factor in the focused crawler's ability of getting more relevant pages. This paper introduces a comprehensive prediction method to address this problem. In this method, a page partition...
The objective of this study is to investigate different pattern classification paradigms in the automatically understanding and characterizing driver behaviors. With features extracted from a driving posture dataset consisting of grasping the steering wheel, operating the shift lever, eating a cake and talking on a cellular phone, created at Southeast University, holdout and cross-validation experiments...
A multivariate process monitoring and fault identification model using decision tree (DT) learning techniques is proposed. We Use one DT classifier for process monitoring and other p (p is the number of the variables) DT classifiers for fault identification. The Mahalanobis distance contours based method for selecting model training samples is proposed to decrease the number of training samples. Numerical...
When training the high-dimension and large-sample objectives, the support vector data description (SVDD) may encounter the curse of dimensionality and may result in large time cost. In order to solve these problems, this paper presents a novel classification algorithm based on rough set and support vector data description (RS-SVDD) by combining the support vector machine (SVM) algorithm with the data...
Support vector machine (SVM) becomes a research focus in the field of machine learning for it is based on expected risk minimization and overcomes “the curse of dimensionality” effectively. In the theoretical research, the focus is mainly on the choice of kernel function and the fast algorithm. On this background, a convex hull algorithm based on Two-Phase method is proposed as one of fast algorithm...
This paper proposes a topic-independent method for automatically scoring essay content. Unlike conventional topic-dependent methods, it predicts the human score of a given essay without training essays written to the same topic as the target essay. To achieve this, this paper introduces a new measure called MIDF that measures how important and relevant a word is in a given essay. The proposed method...
Data mining is a new filed in data processing research. Support vector machine (SVM) is a useful method adopted in data mining. However, when the training set of the SVM contains information of uncertainty, the SVM can do nothing about it. In order to solve the problem presented above, this article discusses an algorithm of nonlinear support vector classification machine based on fuzzy theory. With...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.