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.
Real-time Compressive Tracking (CT) uses the compression sensing theory to provide a new research direction for the target tracking field. The algorithm is simple, efficient and real-time. But there are still shortcomings: tracking results prone to drift phenomenon, cannot adapt to tracking the target scale changes. In order to solve these problems, this paper proposes to use the Kalman filter to...
Identifying and classifying different network applications is very important for trend analysis, dynamic access control, network security and traffic engineering, while traffic classification is able to classify applications effectively. Current popular methods of traffic classification mainly include machine learning algorithm based on supervised or unsupervised and the method based load. In practical...
This paper presents a new face recognition method based on the analysis of local features. Firstly, we can get the images of magnitude by means of analyzing face images with the Gabor wavelets. Secondly, the magnitude images are divided into blocks, then principle components analysis (PCA) could be directly used to all the blocks to construct the feature space. Finally, all the blocks of images are...
A forecast learning method of kernel principal component analysis (KPCA) is presented for specific emitter identification (SEI) application. By constructing a symmetrical decomposition of the kernel matrix, we derived a new algorithm of incremental KPCA. Based on it, the forecast capability is developed by creating dummy samples whose kernel vectors are an extrapolation of the kernel matrix. The advance...
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.