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Flocks, herds, and schools: a distributed behavior model,

by Craig W Reynolds - Proceedings of ACM SIGGRAPH , 1987
"... Abstract The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to script ..."
Abstract - Cited by 1317 (5 self) - Add to MetaCart
to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle system, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose

Ethernet: Distributed packet switching for local computer networks

by Robert M. Metcalfe, David R. Boggs - COMMUN. ACM , 1976
"... Ethernet is a branching broadcast communication system for carrying digital data packets among locally distributed computing stations. The packet transport mechanism provided by Ethernet has been used to build systems which can be viewed as either local computer networks or loosely coupled multipr ..."
Abstract - Cited by 468 (2 self) - Add to MetaCart
Ethernet is a branching broadcast communication system for carrying digital data packets among locally distributed computing stations. The packet transport mechanism provided by Ethernet has been used to build systems which can be viewed as either local computer networks or loosely coupled

Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images.

by Stuart Geman , Donald Geman - IEEE Trans. Pattern Anal. Mach. Intell. , 1984
"... Abstract-We make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice-like physical system. The assignment of an energy function in the physical system determines its Gibbs di ..."
Abstract - Cited by 5126 (1 self) - Add to MetaCart
distribution. Because of the Gibbs distribution, Markov random field (MRF) equivalence, this assignment also determines an MRF image model. The energy function is a more convenient and natural mechanism for embodying picture attributes than are the local characteristics of the MRF. For a range of degradation

Performance Analysis of the IEEE 802.11 Distributed Coordination Function

by Giuseppe Bianchi , 2000
"... Recently, the IEEE has standardized the 802.11 protocol for Wireless Local Area Networks. The primary medium access control (MAC) technique of 802.11 is called distributed coordination function (DCF). DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary slott ..."
Abstract - Cited by 1869 (1 self) - Add to MetaCart
Recently, the IEEE has standardized the 802.11 protocol for Wireless Local Area Networks. The primary medium access control (MAC) technique of 802.11 is called distributed coordination function (DCF). DCF is a carrier sense multiple access with collision avoidance (CSMA/CA) scheme with binary

A bayesian hierarchical model for learning natural scene categories

by Li Fei-fei - In CVPR , 2005
"... We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each region ..."
Abstract - Cited by 948 (15 self) - Add to MetaCart
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each

Example-based learning for view-based human face detection

by Kah-kay Sung, Tomaso Poggio - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1998
"... Abstract—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based “face ” and “nonface ” model clusters. At each image location, a difference feature v ..."
Abstract - Cited by 690 (24 self) - Add to MetaCart
vector is computed between the local image pattern and the distribution-based model. A trained classifier determines, based on the difference feature vector measurements, whether or not a human face exists at   the current image location. We show empirically that the distance metric we adopt

On Sequential Monte Carlo Sampling Methods for Bayesian Filtering

by Arnaud Doucet, Simon Godsill, Christophe Andrieu - STATISTICS AND COMPUTING , 2000
"... In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is develop ..."
Abstract - Cited by 1051 (76 self) - Add to MetaCart
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework

Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach

by Glenn Ellison, Edward L. Glaeser - Journal of Political Economy
"... This paper discusses the prevalence of Silicon Valley–style localiza-tions of individual manufacturing industries in the United States. A model in which localized industry-specific spillovers, natural ad-vantages, and pure random chance all contribute to geographic concentration is used to develop a ..."
Abstract - Cited by 599 (16 self) - Add to MetaCart
This paper discusses the prevalence of Silicon Valley–style localiza-tions of individual manufacturing industries in the United States. A model in which localized industry-specific spillovers, natural ad-vantages, and pure random chance all contribute to geographic concentration is used to develop

Bayesian density estimation and inference using mixtures.

by Michael D Escobar , Mike West - J. Amer. Statist. Assoc. , 1995
"... JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
Abstract - Cited by 653 (18 self) - Add to MetaCart
mixtures of normal distributions. Efficient simulation methods are used to approximate various prior, posterior, and predictive distributions. This allows for direct inference on a variety of practical issues, including problems of local versus global smoothing, uncertainty about density estimates

Brain magnetic resonance imaging with contrast dependent on blood oxygenation.

by S Ogawa , T M Lee , A R Kay , D W Tank - Proc. Natl. Acad. Sci. USA , 1990
"... ABSTRACT Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with imag ..."
Abstract - Cited by 648 (1 self) - Add to MetaCart
the vessel wall. This increase in the number of spins affected by deoxyhemoglobin is a form of amplification. When the susceptibility-induced local field differences exist within an imaging voxel, there is a resultant distribution of shifts in water resonance frequencies. In the gradient-echo method, a phase
Results 1 - 10 of 21,258