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.
Recent progress in using long short-term memory (LSTM) for image captioning has motivated the exploration of their applications for video captioning. By taking a video as a sequence of features, an LSTM model is trained on video-sentence pairs and learns to associate a video to a sentence. However, most existing methods compress an entire video shot or frame into a static representation, without considering...
For the task of image annotation, traditional probabilistic topic models based on Latent Dirichlet Allocation (LDA) [1], assume that an image is a mixture of latent topics. An inevitable limitation of LDA is the inability to model topic correlation since topic proportions of an image are generated independently. Motivated by Correlated Topic Model (CTM) [2] which derives from natural language processing...
For the task of image annotation, traditional methods based on probabilistic topic model, such as correspondence Latent Dirichlet Allocation (corrLDA) [1], assumes that image is a mixture of latent topics. However, this kind of models is unable to directly model correlation between topics since topic proportions of an image are generated independently. Our model, called correspondence Correlated Topic...
Research finds within the last decade on network measurement have shown the classical assumption of exponentially decaying service distributions does not apply in a number of sources - Ethernet, ISDN, CCSN and VBR video. Recent research has shown that self-similar nature of traffic still exists in the traffic of wireless networks. Appropriate service distribution of these sources may be heavy-tailed...
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.