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, new statistical learning algorithms with kernel function are presented. Recently, iterative learning algorithms for obtaining eigenvectors in the principal component analysis (PCA) have been presented in the field of pattern recognition and neural network. However, the Fisher linear discriminant analysis (FLDA) has been used in many fields, especially face image analysis. The drawback...
In this paper , we propose a new statistical learning algorithm. This study quantitatively verifies the effectiveness of its feature extraction performance for face information processing. Simple-FLDA is an algorithm based on a geometrical analysis of the Fisher linear discriminant analysis. As a high-speed feature extraction method, the present algorithm in this paper is the improved version of Simple-FLDA...
In this paper, we illustrate a decision support system of modeling the room designs suited for personal preference. The preference to colors is differed to individual personality. Nevertheless, modeling the room design is depended on the designer's sensitivity until now. Therefore, the technique of modeling the various room designs people satisfy is needed. In this paper, we propose automatic modeling...
In a field of pattern recognition, researches of feature extraction and dimension reduction using the Simple-PCA that is an approximation algorithm of the principal component analysis (PCA) are actively conducted. In such a statistical method, a lot of algorithms that perform incremental learning by using new incremental data exist. For example, there is an algorithm named Incremental PCA for PCA...
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.