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.
images with their surrounding text are collected from a few photo forums to support this approach. The entire process is formulated in a divide-and-conquer framework where a query keyword is provided along with the uncaptioned image to improve both the effectiveness and efficiency. This is helpful when the collected data
This paper presents a new method of automatic image annotation based on visual cognitive theory that improves the accuracy of image recognition by taking two semantic levels of keywords that give feedback to each other into consideration. Our system first segments an image and recognizes objects in the K-Nearest
the actual content of the image. The term dasiacontentpsila in this context might refer to colors, shapes, textures, or any other information that can be derived from the image itself. Without the ability to examine image content, search must rely on metadata such as captions or keywords, which may be laborious or
In order to enable more effective image retrieval via keywords, automatic image annotation and categorization becomes an important problem in computer vision and content based image retrieval. Unfortunately, there exists a semantic gap between the low-level feature vectors and the high-level semantics or concepts. In
-based image retrieval. CBIR is the application of computer vision to the image retrieval problem, which analyzes the actual contents of the images themselves rather than relying on annotations or keywords generated by human labor. Without textual descriptions or label information, successful retrieval of relevant images
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.