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, an adaptive recognition model (ARM) is proposed for image annotation. The ARM consists of an adaptive classification network (CFN) and a nonlinear correlation network (CLN). The adaptive CFN aims to annotate an image with keywords, and the CLN is used to unveil the correlative information of keywords
was by keyword indexing, or simply by browsing. Digital images databases however, open the way to content-based searching. In this paper we survey some technical aspects of current content-based image retrieval systems based on several neural network architectures. Firstly we discuss the image retrieval system based on
In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a textile. Here we use 10 Kobayashi emotion keywords. Our method is composed of feature extraction and classification. For accurate emotion recognition, both color and pattern are extracted from a
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.