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.
In order to solve the problems of current machine learning in fault diagnosing system of the chemical plants, a better and effective multilayer architecture model is used in this paper. Hidden Markov model (HMM) is good at dealing with dynamic continuous data and support vector machine (SVM) shows superior performance for classification, especially for limited samples. Combining their respective virtues,...
A new method of facial representation proposed for face recognition by support vector machine (SVM). For face representation we have used a five-step multiresolution method, namely the two-dimensional discrete wavelet transform (DWT) is used to transform the faces to a more discriminated space and then use the approximations of subimages in each scale as feature points to classify different faces...
Jsteg and F5 are two typical steganography methods of JPEG images and have been used widely. To distinguish F5 stego images and Jsteg stego images, a classification algorithm based on sensitive features and SVM classifier is presented, where the sensitive features are extracted from the subband coefficients of those stego-images and the subband coefficients are obtained by wavelet packet decomposition...
The way that Alzheimer's disease (AD) invades brain is to destroy its fundamental elements, i.e. neurons. The phenomenon of neuron destruction reflects volume changes on brain tissues such as gray matter, white matter and cerebro-spinal fluid. In the AD-related research, the volumetric analysis of hippocampus is the most extensive study. However, the segmentation and identification of the hippocampus...
This paper presents a non-intrusive fatigue detection system based on the video analysis of drivers. The system relies on multiple visual cues to characterize the level of alertness of the driver. The parameters used for detecting fatigue are: eye closure duration measured through eye state information and yawning analyzed through mouth state information. Initially, the face is located through Viola-Jones...
A novel chaotic immune algorithm (CImmune) is proposed to implement for parameter selection of Support Vector Regression (SVR). After adding chaotic local searching to the artificial immune procedure for parameter optimization of SVR, this method takes the advantages of both Chaos Optimization Algorithm (COA) and Artificial Immune Algorithm (AIA) to improve the effect of SVR efficiently. From experiments...
Support Vector Machines (SVM) is a powerful classification technique in data mining and has been successfully applied to many real-world applications. Parameter selection of SVM will affect classification performance much during training process. However, parameter selection of SVM is usually identified by experience or grid search (GS). GS is simple and easily implemented, but it is very time-consuming...
Scientific documents are unstructured data consisting of natural language and hard for scientists to read and manage. Keywords are very helpful for scientists to search the related documents and know about their contents in a prompt way. In this paper we investigate a kind of data preprocessing technique used in SVM-based keyword extraction from scientific documents. Four definitions of regular scientific...
We propose a hybrid approach of support vector regression, genetic algorithm, and seasonal moving window to explore seasonality effect for the stock indexes in three developed and one emerging markets using daily prices from 1996 to 2005. First, we utilize genetic algorithm to locate the approximate optimal combination of technical indicators. Then the property of nonlinearity and high dimensionality...
In this paper, we propose some machine learning techniques for the acquisition of subcategorization frames (SCFs) information from parsed corpora for Chinese. A smoothing algorithm is used in order to minimize mistake caused by falsely parsing. Our algorithm is based on Support Vector Machines to filter improper SCFs extracted from low quality corpora parsed by dependency parser which we show give...
This paper reports experiments on topic extraction in Chinese documents using a feature set enriched with Word Sense Disambiguation (WSD) as semantic information. The results of these experiments suggest that incorporating WSD information into Chinese topic extraction tasks may yield improvements over models which do not use WSD information.
There exists numerous news obviously classified into incorrect categories on Chinese Web pages portals. For example, the news dated Aug 13, 2008 with title of "An 78 year-old man completed his Bachelor's degree" is classified incorrectly into class politics at Taiwan Yahoo Web site. This phenomenon is owing to mainly the difficulty in automatically classifying Chinese news and the fact that...
In this paper, we describe a location based text mining approach to classify texts into various categories based on their geospatial features, with the aims to discovering relationships between documents and zones. We first mapped documents into corresponding zones by adaptive affinity propagation (adaptive AP) clustering technique, and then framed maximize zones by means of simplified fuzzy ARTMAP...
A new QSAR model for the classification of estrogen receptor-?? (ER??) selective ligand has been developed with adaptive boosting (Adaboost) and support vector machine (SVM). Compound structures were drawn in Molinspiration WebME Editor and imported into the E-Dragon 1.0 software to calculate seven categories descriptors. The selection of variables for each descriptor was performed with particle swarm...
Breast cancer is the most common cancer diagnosed among U.S. women. In this paper we have done some experiments for tumor detection in digital mammogram images. First of all, we have described a method that segments the breast image automatically. As a preprocessing, we have used fuzzy based noise removal filter that removes noise. Then for segmentation, we have provided a background removal method...
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.