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.
An automatic target recognition (ATR) system based on rough set-support vector machine (RS-SVM) for SAR targets is proposed in this paper. The system combines the strong feature selection ability of rough set (RS) with the excellent classification ability of SVM together. The wavelet invariant moments firstly are extracted, then selected by using forward greedy numeral attribute reduction algorithm...
Quality evaluation and classification is very important for crop market price determination. A lot of methods have been applied in the field of quality classification including principal component analysis (PCA) and artificial neural network (ANN) etc. The use of ANN has been shown to be a cost-effective technique. But their training is featured with some drawbacks such as small sample effect, black...
The kernel function and parameters selection is a key problem in the research of support vector machine. After discussing the influence of support vector machine on kernel parameters and error penalty factors, a new kernel function CombKer was proposed and constructed. The CombKer kernel function is a kind of combination kernel function, which combines the Gaussian RBF kernel function that has the...
The objective of this study was to develop a computerized empty glass bottle inspection method in an attempt to replace manual inspection. The inspection system structure based on machine vision was illustrated in the article. Morphologic methods and wavelet transform were used to extract features of the bottle body and the finish from images. The fuzzy support vector machine neural network was adopted...
This paper proposes a novel method for facial expression recognition by using independent component analysis of Gabor features. In the feature extraction stage, Gabor feature vectors are firstly extracted from a set of facial expressions images, then using independent component analysis (ICA) to extract the independent Gabor features. After that, the independent Gabor features are used to train SVM...
As an effective tool in pattern recognition and machine learning, support vector machine (SVM) has been adopted abroad. In developing a successful SVM classifier, eliminating noise and extracting feature are very important. This paper proposes the application of kernel PCA to SVM for feature extraction. Then PSO Algorithm is adopted to optimization of these parameters in SVM. The novel time series...
With the increase of the training set??s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel pre-extracting method for SVM classification is proposed in this paper. In SVM classification, only support vectors (SVs) have significant influence on the optimization result. We adopt a non-parametric k-NN rule called relative neighborhood graph...
Clustered microcalcification is an important signal for breast cancer in the early stages. In this paper, we propose a multiple kernel SVM with group features (GF-SVM) to tackle problems associated with heterogeneous features of clustered microcalcification and normal breast tissues in suspicious regions. Specifically, different types of features such as being gradient, geometric and textural are...
To improve the learning and generalization ability of the machine-learning model, a new compound kernel that may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the new compound kernel support vector machine to a speech recognition system for Chinese isolated words, non-specific person and middle glossary quantity, and compared the speech...
Distribution centers site selection has become a popular problem in recent years. Fine distribution centers site selection can ensure the supply and reduce the cost. By studying the methods proposed by other scholars, a mew method, KPCA (kernel principal component analysis) -SVRM (support vector regression machine) is proposed by this paper. The first step of this method is to apply KPCA to SVRM for...
A new feature extraction method for high dimensional data using least squares support vector regression (LSSVR) is presented. Firstly, the expressions of optimal projection vectors are derived into the same form as that in the LSSVR algorithm by specially extending the feature of training samples. So the optimal projection vectors could be obtained by LSSVR. Then, using the kernel tricks, the data...
This paper presents a computer-aided diagnosis (CAD) system for automatic detection of clustered microcalcifications (MCs) in digitized mammograms. The proposed system consists of two main steps. First, potential microcalcification pixels in the mammograms are segmented out by using 4 mixed features consisting of two wavelet features and two gray level statistical features and then the potential microcalcification...
We propose a feature selection criterion based on kernel discriminant analysis (KDA) for a n-class problem, which finds eigenvectors on which the projected class data are locally maximally separated. The proposed criterion is the sum of the objective function values of KDA associated with the n-1 eigenvectors. The criterion results in calculating the sum of n-1 eigenvalues associated with the eigenvectors...
There is an important military significance about aircrafts type recognition based on shortwave communication. Acoustic signals received by shortwave radio about aircrafts are complex and they contain some valuable information. It is very difficult to identify the aircraft type based on background sound signals of shortwave communication. In order to solve this problem, in this paper two methods for...
In this paper we describe a model for classifying binary data using classifiers based on Bernoulli mixture models. We show how Bernoulli mixtures can be used for feature extraction and dimensionality reduction of raw input data. The extracted features are then used for training a classifier for supervised labeling of individual sample points. We have applied this method to two different types of datasets,...
One of the Internetpsilas hallmark is the rapid spread of the use of information and communication technology. This has boosted methods for hiding stego information inside digital cover content images which is a concerning issue in information security. On the other hand, attack of steganographic schemes has leveraged methods for steganalysis which is a challenging problem. In this paper, first we...
Facial expression recognition has received more and more attentions during the last two decades. A variety of recognition techniques have been applied in various applications. In this paper, a novel expression recognition technique is proposed based on a state-of-the-art classifier called minimax probability machine (MPM). After introducing some technical details of preprocessing and feature extraction,...
This paper presents a novel approach to microcalcification clusters (MCs) detection in mammograms based on the tensor subspace learning and twin support vector machines (TWSVMs). The ground truth of MCs in mammograms is assumed to be known as a priori. First each MCs is enhanced by using a simple artifact removal filter and a well designed high-pass filter. Then the tensor subspace learning algorithms,...
In this work efficiency of feature extraction methods based on linear wavelet transform and merged wavelet packets technique are evaluated relatively with different supervised classification methods. Experimental heart arrthymia data has been obtained from MIT-BIH arrthymia database. Total of 1200 training and 1200 test samples have been chosen equally for 6 classes from the database. For the purpose...
Distinct from conventional techniques where the neural network (NN) is employed to solve the problem of paper currency verification, in this paper, we shall present a novel method by applying the support vector machine (SVM) approach to distinguish counterfeit banknotes from genuine ones. On the basis of the statistical learning theory, SVM has better generalization ability and higher performance...
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.