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.
High-dimensional data are ubiquitous in most real-world research areas, such as machine learning, image processing and so on. Actually, high-dimensional data that belong to the same classes tend to gather in their own low-dimensional subspaces. Recently, many subspace recovery algorithms based on the sparse representation such as Sparse Subspace Clustering (SSC), Low-Rank Representation (LRR) and...
With the rapid expansion of data scale, big data mining and analysis have attracted increasing attention. Outlier detection as an important task of data mining is widely used in many applications. However, conventional outlier detection methods have difficulty handling large-scale datasets. In addition, most of them typically can only identify global outliers and are over sensitive to parameters variation...
Speeded Up Robust Features (SURF) is one of the most robust and widely used image matching algorithms based on local features. However, the performance for rotation image is poor when one image is a rotated version of the other. To improve the matching accuracy of rotation image, we present an modified image matching algorithm combining Haar wavelet and the rotation invariant Local Binary Patterns...
With the rapid expansion of data scale, big datamining and analysis has attracted increasing attention. Outlierdetection as an important task of data mining is widely usedin many applications. However, conventional outlier detectionmethods have difficulty handling large-scale datasets. In addition, most of them typically can only identify global outliersand are over sensitive to parameters variation...
In this paper, complex network theory is used to generate robust scale-free topology for wireless sensor networks (WSNs). Nodes in WSNs consume energy in two stages: network generation and network operation. Existing scale-free models for WSNs focus on the energy in the first stage. However, sensors consume most energy in the second stage. This paper proposes a method called flow-aware scale-free...
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.