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.
Pedestrian detection and semantic segmentation are highly correlated tasks which can be jointly used for better performance. In this paper, we propose a pedestrian detection method making use of semantic labeling to improve pedestrian detection results. A deep learning based semantic segmentation method is used to pixel-wise label images into 11 common classes. Semantic segmentation results which...
Land cover classification is a task that requires methods capable of learning high-level features while dealing with high volume of data. Overcoming these challenges, Convolutional Networks (ConvNets) can learn specific and adaptable features depending on the data while, at the same time, learn classifiers. In this work, we propose a novel technique to automatically perform pixel-wise land cover classification...
In this paper we discuss certain theoretical properties of the algorithm selection approach to the problem of semantic segmentation in computer vision. We show that an algorithm's score depends on final task. Thus to properly evaluate an algorithm and to determine its suitability, precise score value obtained on well formulated tasks can be used only. When an algorithm suitability is well known, the...
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.