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 this paper, a novel spectral-spatial very high resolution images shadow detection algorithm based on random walker is proposed. First, a set of training samples is obtained by an improved Otsu based thresholding method automatically. Then, a widely used pixel-wise classifier, i.e., the Support Vector Machine (SVM), is applied to obtain an initial binary classification map. Finally, the initial...
In this paper, a decision fusion of pixel-level and superpixel-level classifiers (DFPSC) for the HSI is proposed. First, the support vector machine based classification probability combined with the local spatial information is introduced to classify the HSI in a pixel-by-pixel manner. Then, the HSI is over-segmented into non-overlapping superpixels. Each superpixel contains spatially-connected and...
In this paper, we propose a support vector machine (SVM) ensemble classification method. Firstly, dataset is preprocessed by Wilcoxon rank sum test to filter irrelevant genes. Then one SVM is trained using the training set, and is tested by the training set itself to get prediction results. Those samples with error prediction result or low confidence are selected to train the second SVM, and also...
Parameter settings of support vector machine (SVM) have a great influence on its performance. Grid search combining with cross-validation and numerical methods by minimizing some generalization error bounds are two usually adopted methods to tune the multiple parameters in SVM. However, the grid search is often time-consuming, especially when dealing with multiple parameters while the numerical methods...
In this paper, an efficient approach for tablets vision inspection is proposed, which can detect missing and broken individual tablets in each blister after they are sealed. The images of tablets in blister can be obtained clearly using multi-lights. From these images the regions of tablets are segmented through thresholding method, and the tablets' shape contours are obtained by Canny edge detector...
A novel region-based color mapping method is proposed to render fused image of visible and infrared (IR). The method is based on image segmentation, region recognition, image fusion and color transfer. Firstly visible image and IR image are fused based on the curvelet transform. At the same time, a color database is formed by grouping a set of natural color images according to their scene contents...
Selecting high discriminative genes from gene expression data has become an important research. Not only can this improve the performance of cancer classification, but it can also cut down the cost of medical diagnoses when a large number of noisy, redundant genes are filtered. In this paper, a hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) method is used for gene selection, and...
The automatic recognition of human face presents a significant challenge to the pattern recognition research community recently. As a traditional method for face recognition, principal component analysis (PCA) may neglect differentia. Since kernel partial least squares (KPLS) creates orthogonal score vectors by using the existing correlations and keeps most of the variance between different classes,...
The main problems in tissue classification by using DNA Microarray data are selecting genes relevant for a given tumor and constructing the optimized classifiers. This paper proposes a new gene selection and tissue classification method based on support vector machines and genetic algorithm. Firstly, the Wilcoxon-test is used as a coarse gene selection method to remove most of the irrelevant genes...
Gene selection is an important problem in microarray data processing. A new gene selection method based on Wilcoxon rank sum test and support vector machine (SVM) is proposed in this paper. First, Wilcoxon rank sum test is used to select a subset. Then each selected gene is trained and tested using SVM classifier with linear kernel separately, and genes with high testing accuracy rates are chosen...
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.