Results 1 - 10 of 5,497

A density-based algorithm for discovering clusters in large spatial databases with noise

by Martin Ester, Hans-Peter Kriegel, Jörg Sander, Xiaowei Xu , 1996
"... Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clu ..."
Abstract - Cited by 1786 (70 self) - Add to MetaCart
Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery

Efficient and Effective Clustering Methods for Spatial Data Mining

by Raymond T. Ng, Jiawei Han , 1994
"... Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering methods have a role to play in spatial data mining. To this end, we develop a new clustering method called CLARANS which ..."
Abstract - Cited by 709 (37 self) - Add to MetaCart
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering methods have a role to play in spatial data mining. To this end, we develop a new clustering method called CLARANS which

Randomized Gossip Algorithms

by Stephen Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah - IEEE TRANSACTIONS ON INFORMATION THEORY , 2006
"... Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
Abstract - Cited by 532 (5 self) - Add to MetaCart
Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join

Linear spatial pyramid matching using sparse coding for image classification

by Jianchao Yang, Kai Yu, Yihong Gong, Thomas Huang - in IEEE Conference on Computer Vision and Pattern Recognition(CVPR , 2009
"... Recently SVMs using spatial pyramid matching (SPM) kernel have been highly successful in image classification. Despite its popularity, these nonlinear SVMs have a complexity O(n 2 ∼ n 3) in training and O(n) in testing, where n is the training size, implying that it is nontrivial to scaleup the algo ..."
Abstract - Cited by 497 (21 self) - Add to MetaCart
the algorithms to handle more than thousands of training images. In this paper we develop an extension of the SPM method, by generalizing vector quantization to sparse coding followed by multi-scale spatial max pooling, and propose a linear SPM kernel based on SIFT sparse codes. This new approach remarkably

Fastmap: A fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets

by Christos Faloutsos, King-Ip (David) Lin , 1995
"... A very promising idea for fast searching in traditional and multimedia databases is to map objects into points in k-d space, using k feature-extraction functions, provided by a domain expert [Jag91]. Thus, we can subsequently use highly fine-tuned spatial access methods (SAMs), to answer several ..."
Abstract - Cited by 502 (22 self) - Add to MetaCart
types of queries, including the `Query By Example' type (which translates to a range query); the `all pairs' query (which translates to a spatial join [BKSS94]); the nearest-neighbor or best-match query, etc. However, designing feature extraction functions can be hard. It is relatively

High performance scalable image compression with EBCOT

by David Taubman - IEEE Trans. Image Processing , 2000
"... A new image compression algorithm is proposed, based on independent Embedded Block Coding with Optimized Truncation of the embedded bit-streams (EBCOT). The algorithm exhibits state-of-the-art compression performance while producing a bit-stream with a rich feature set, including resolution and SNR ..."
Abstract - Cited by 586 (11 self) - Add to MetaCart
A new image compression algorithm is proposed, based on independent Embedded Block Coding with Optimized Truncation of the embedded bit-streams (EBCOT). The algorithm exhibits state-of-the-art compression performance while producing a bit-stream with a rich feature set, including resolution and SNR

The X-tree: An index structure for high-dimensional data

by Stefan Berchtold, Daniel A. Keim, Hans-peter Kriegel - In Proceedings of the Int’l Conference on Very Large Data Bases , 1996
"... In this paper, we propose a new method for index-ing large amounts of point and spatial data in high-dimensional space. An analysis shows that index structures such as the R*-tree are not adequate for indexing high-dimensional data sets. The major problem of R-tree-based index structures is the over ..."
Abstract - Cited by 592 (17 self) - Add to MetaCart
In this paper, we propose a new method for index-ing large amounts of point and spatial data in high-dimensional space. An analysis shows that index structures such as the R*-tree are not adequate for indexing high-dimensional data sets. The major problem of R-tree-based index structures

Mega: molecular evolutionary genetic analysis software for microcomputers

by Sudhir Kumar, Koichiro Tamura, Masatoshi Nei - CABIOS , 1994
"... A computer program package called MEGA has been developed for estimating evolutionary distances, reconstructing phylogenetic trees and computing basic statistical quantities from molecular data. It is written in C+ + and is intended to be used on IBM and IBM-compatible personal computers. In this pr ..."
Abstract - Cited by 505 (10 self) - Add to MetaCart
, new algorithms of branch-and-bound and heuristic searches are implemented. In addition, MEGA computes statistical quantities such as nucleotide and amino acid frequencies, transition/transversion biases, codon frequencies (codon usage tables), and the number of variable sites in specified segments

Scale-space and edge detection using anisotropic diffusion

by Pietro Perona, Jitendra Malik - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1990
"... Abstract-The scale-space technique introduced by Witkin involves generating coarser resolution images by convolving the original image with a Gaussian kernel. This approach has a major drawback: it is difficult to obtain accurately the locations of the “semantically mean-ingful ” edges at coarse sca ..."
Abstract - Cited by 1887 (1 self) - Add to MetaCart
scales. In this paper we suggest a new definition of scale-space, and introduce a class of algorithms that realize it using a diffusion process. The diffusion coefficient is chosen to vary spatially in such a way as to encourage intraregion smoothing in preference to interregion smoothing. It is shown

Efficient Processing of Spatial Joins Using R-Trees

by Thomas Brinkhoff, Hans-peter Kriegel, Bernhard Seeger , 1993
"... Abstract: In this paper, we show that spatial joins are very suitable to be processed on a parallel hardware platform. The parallel system is equipped with a so-called shared virtual memory which is well-suited for the design and implementation of parallel spatial join algorithms. We start with an a ..."
Abstract - Cited by 363 (14 self) - Add to MetaCart
Abstract: In this paper, we show that spatial joins are very suitable to be processed on a parallel hardware platform. The parallel system is equipped with a so-called shared virtual memory which is well-suited for the design and implementation of parallel spatial join algorithms. We start
Results 1 - 10 of 5,497