In this paper, we present optimal parallel algorithms for optical clustering on a mesh-connected computer. Optical clustering is a clustering technique based on the principal of optical resolution, and is of particular interest in picture analysis. The algorithms we present are based on the application of parallel algorithms in computational geometry and graph theoryl In particular, we show that given a set S of N points in the Euclidean plane, the following problems can be solved in optimal O(x/-N) time on a mesh-connected computer of size N. 1. Determine the optical clusters of S with respect o a given separation parameter. 2. Given an interval [a,b] representing the number of optical clusters desired in the clustering of S, determine the...
Clustering is a classical data analysis technique that is applied to a wide range of applications in...
On a mesh-connected computer, moving data across the mesh is the most time-consuming operation in ma...
In this thesis we study efficient computational methods for geometrical problems of practical import...
A digitized plane Π of size M is a rectangular √M × √M array of integer lattice points called pixels...
In this paper we study parallel algorithms for the Mesh-of-Processors architecture to solve visibili...
We present a number of computational complexity results for an optical model of computation called ...
Abstract. Clustering is a classical data analysis technique that is applied to a wide range of appli...
AbstractÐIn k-means clustering, we are given a set of n data points in d-dimensional space Rd and an...
This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spa...
Parallel algorithms to solve several computational geometric problems on mesh-connected computers (M...
A k-clustering of a given set of points in the plane is a partition of the points into k subsets ("c...
A k-clustering of a given set of points in the plane is a partition of the points into k subsets (&q...
In some Computer Vision applications there is the need for grouping, in one or more clusters, only a...
In some Computer Vision applications there is the need for grouping, in one or more clusters, only a...
OPTICS is a hierarchical density-based data clustering algorithm that discovers arbitrary-shaped clu...
Clustering is a classical data analysis technique that is applied to a wide range of applications in...
On a mesh-connected computer, moving data across the mesh is the most time-consuming operation in ma...
In this thesis we study efficient computational methods for geometrical problems of practical import...
A digitized plane Π of size M is a rectangular √M × √M array of integer lattice points called pixels...
In this paper we study parallel algorithms for the Mesh-of-Processors architecture to solve visibili...
We present a number of computational complexity results for an optical model of computation called ...
Abstract. Clustering is a classical data analysis technique that is applied to a wide range of appli...
AbstractÐIn k-means clustering, we are given a set of n data points in d-dimensional space Rd and an...
This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spa...
Parallel algorithms to solve several computational geometric problems on mesh-connected computers (M...
A k-clustering of a given set of points in the plane is a partition of the points into k subsets ("c...
A k-clustering of a given set of points in the plane is a partition of the points into k subsets (&q...
In some Computer Vision applications there is the need for grouping, in one or more clusters, only a...
In some Computer Vision applications there is the need for grouping, in one or more clusters, only a...
OPTICS is a hierarchical density-based data clustering algorithm that discovers arbitrary-shaped clu...
Clustering is a classical data analysis technique that is applied to a wide range of applications in...
On a mesh-connected computer, moving data across the mesh is the most time-consuming operation in ma...
In this thesis we study efficient computational methods for geometrical problems of practical import...