相关论文: Cluster Detection in Astronomical Databases: the A…

We describe the construction of catalogues of galaxy clusters from the APM Galaxy survey using an automated algorithm based on Abell-like selection criteria. We investigate the effects of varying several parameters in our selection…

A geometrical pattern is a set of points with all pairwise distances (or, more generally, relative distances) specified. Finding matches to such patterns has applications to spatial data in seismic, astronomical, and transportation…

Clustering large spatial databases is an important problem, which tries to find the densely populated regions in a spatial area to be used in data mining, knowledge discovery, or efficient information retrieval. However most algorithms have…

Within scientific and real life problems, classification is a typical case of extremely complex tasks in data-driven scenarios, especially if approached with traditional techniques. Machine Learning supervised and unsupervised paradigms,…

The APM Cluster Survey was based on a modification of Abell's original classification scheme for galaxy clusters. Here we discuss the results of an investigation of the stability of the statistical properties of the cluster catalogue to…

The ACS Survey of Globular Clusters has used HST's Wide-Field Channel to obtain uniform imaging of 65 of the nearest globular clusters to provide an extensive homogeneous dataset for a broad range of scientific investigations. The survey…

Galaxy groups provide the means for a great diversity of studies that contribute to a better understanding of the structure of the universe on a large scale and allow the properties of galaxies to be linked to those of the host halos.…

Clustering aims to group unlabeled objects based on similarity inherent among them into clusters. It is important for many tasks such as anomaly detection, database sharding, record linkage, and others. Some clustering methods are taken as…

Context: The huge and still rapidly growing amount of galaxies in modern sky surveys raises the need of an automated and objective classification method. Unsupervised learning algorithms are of particular interest, since they discover…

Clustering, or grouping, dataset elements based on similarity can be used not only to classify a dataset into a few categories, but also to approximate it by a relatively large number of representative elements. In the latter scenario,…

The paper considers the problem of anomaly detection in 3D images of fibre materials. The spatial Stochastic Expectation Maximisation algorithm and Adaptive Weights Clustering are applied to solve this problem. The initial 3D grey scale…

One important tool is the optimal clustering of data into useful categories. Dividing similar objects into a smaller number of clusters is of importance in many applications. These include search engines, monitoring of academic performance,…

The paper tackles the problem of clustering multiple networks, directed or not, that do not share the same set of vertices, into groups of networks with similar topology. A statistical model-based approach based on a finite mixture of…

This article explains an optimization-based approach for counting and localizing stars within a small cluster, based on photon counts in a focal plane array. The array need not be arranged in any particular way, and relatively small numbers…

We introduce the Unified Cluster Catalogue, the largest catalogue of stellar clusters currently listing nearly 14000 objects. In this initial release it exclusively contains Milky Way open clusters, with plans to include other objects in…

Clustering large, mixed data is a central problem in data mining. Many approaches adopt the idea of k-means, and hence are sensitive to initialisation, detect only spherical clusters, and require a priori the unknown number of clusters. We…

We present a new galaxy cluster search in the COSMOS field through the use of the Adaptive Matched Identifier of Clustered Objects (AMICO). We produced a new cluster and group catalogue up to $z=2$, by performing an innovative application…

Clusters of galaxies need to be investigated using complementary approaches combining all currently available observational techniques (X-ray, gravitational lensing, dynamics, SZ) on homogeneous samples if one wants to understand their…

We present the results of methodological works on automated analysis of the large scale distribution of galaxies. Selecting candidates for clusters and groups of galaxies was carried out using two complementary methods of determining the…

Based on a recent photometric redshift galaxy catalogue, we have searched for galaxy clusters in the Stripe~82 region of the Sloan Digital Sky Survey by applying the Adami & MAzure Cluster FInder (AMACFI). Extensive tests were made to…