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 advances in using computer with different fields of sciences produced huge amounts of data. These data represent as an analysis tool and key to overcome many problems. Clustering is a primary process to analyze the data as well as, it's a preprocessing step before other techniques like classification. Density-Based clustering algorithms have advantages like clustering any arbitrary shapes and...
In the extraction of halftone anti-counterfeiting information, the image maybe skew, which causes the anti-counterfeiting information cannot be extracted. Using dots characters to construct the synchronous information, we propose a halftone dots detection algorithm based on cluster analysis. This algorithm detects dots with different in the halftone images, then extract the synchronous information...
Big data denotes to data volumes in the range of zettabytes (1021) and beyond. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s, as of 2012, every day 2.5 exabytes (2.5×1018) of data were created, as of 2014, every day 2.3 zettabytes (2.3×1021) of data were created [4, 5]. Every year, NASA and the National Science Foundation host...
A novel Polarimetric-Texture-Structure descriptor for high-resolution PolSAR image is presented in this paper. More precisely, a PolSAR image is represented by a tree of shapes, each of which is associated with several polarimetric and texture attributes. We first extract the texture properties and polarimetric characteristics from each shape, then use the shape co-occurrence patterns (SCOPs) to characterize...
Lane detection is a critical step in advanced driver assistance systems (ADAS). The detected lane information is used by later modules of warning and controlling the differential brake and steering angle. Here we propose an efficient algorithm for detecting accurate lane inbounds under varying illumination and road conditions like curvy, straight and dashed lane markings, deterministically. The current...
Building boundary identification is an essential prerequisite in building outline generation from point cloud data. In this problem, boundary edges that constitute the building boundary are identified. The existing solutions to the identification of boundary edges from the input point set have one or more of the following problems: ineffective in finding appropriate edges in a concave shape, incapable...
Clustering algorithm can be used for exploring deep information from data base and outlining the characteristics of each class. In this paper, some typical clustering algorithms were reviewed. Then we focused on classifying G-band bright points (GBPs) in high resolution solar photospheric images. It is found that K-means is suitable for detecting the noise points and DBSCAN algorithm is good at extracting...
Data clustering is one of the popular tasks recently used in the educational data mining arena for grouping similar students by several aspects such as study performance, behavior, skill, etc. Many well-known clustering algorithms such as k-means, expectation-maximization, spectral clustering, etc. were employed in the related works for educational data clustering. None of them has taken into consideration...
Processing surfaces with data coming from an automatic acquisition technique always generates the problem of unorganized 3D point sets or presence of geometric deficiencies (i.e. in some regions of the surface, the obtained data points are sparse or without containing any points). It leads to what we call "holes", and a mandatory surface reconstruction process. Applying the process to the...
Mobility management is an essential feature of cellular networks. High accuracy of mobile user positioning is needed to handle mobility efficiently enough and bad cell data can harm this feature significantly. Inaccuracy of cell shapes, lack of cell data measurements, and inaccurate coordination in a geographical area are major shortcomings when it comes to positioning of mobile users in cellular...
Discovering changes in the data distribution of streams and discovering recurrent data distributions are challenging problems in data mining and machine learning. Both have received a lot of attention in the context of classification. With the ever increasing growth of data, however, there is a high demand of compact and universal representations of data streams that enable the user to analyze current...
The unsupervised analysis of data-sets, both large in dimension as well as in number of objects, are one of the most challenging tasks in data intense sciences. Especially in astronomy, dedicated survey telescopes generate an enormous amount of complex data. For example the database of the Sloan Digital Sky Survey (SDSS DR10) contains 3 million spectra with ca. 5,000 values each. Analyzing those spectra...
Shapelet is a fragment of a time series that can be used to represent class characteristics of the time series. Its application in time series classification is extensively discussed and many improvements have been made. One of them is to separate the construction of classifier from shapelet selection process which is called shapelet transformation. It is more flexible and provides us with more freedom...
This paper proposed an automatic clustering algorithm based on entropy for discovering the interest pattern over users' web log. We introduced the information entropy on the basis of clustering algorithm. Compared with traditional clustering algorithms, our method does not require any parameters specified by the end user. Meanwhile, it can discover the clusters in arbitrary shape and size. Experimental...
Integrating legacy plant and process information into engineering, control, and enterprise systems may significantly increase the efficiency of managerial and technical operations in industrial facilities. The first step towards the pursued data integration is the extraction of relevant information from existing engineering documents, many of which are stored in vector-graphics-compatible formats...
This paper evaluates the feasibility of using the fusion of multispectral data from a Kinect v2 sensor as a way to extract the palm region of hand in an unconstrained environment. The depth data was used to both track the hand and extract palm regions. This extracted palm region was then used to extract the palm region in the RGB and Near Infrared data. One of the underlying goals was to maintain...
The demand for automated 3D road bounderies extraction is driven by the importance of maintaining and updating the fundamental geographic data of road for for various applications that support urban planning, traffic control, emergency response. Mobile laser scanning (MLS) as a promising technology for the rapid 3D mapping of road environment, provides a good means to capture every detail along the...
Distributed data mining techniques and mainly distributed clustering are widely used in the last decade because they deal with very large and heterogeneous datasets which cannot be gathered centrally. Current distributed clustering approaches are normally generating global models by aggregating local results that are obtained on each site. While this approach mines the datasets on their locations...
The dynamic behavior of large interconnected power systems can be provided by wide-area measurement systems. Motivated by this, the use of on-line techniques has been developed, as well as multivariate methods have been proposed to extract useful patterns from a large data set. In this paper, a multivariable technique to identify and extract dynamic patterns from simultaneously measured data is proposed...
In this paper we propose a method to locate inloop repetitions in a video. An in-loop repetition consists in repeating the same action(s) many times consecutively. The proposed method adapts and uses the auto-correlation method YIN, originally proposed to find the fundamental frequency in audio signals. Based on this technique, we propose a method that generates a matrix where repetitions correspond...
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.