Results 1 - 10 of 437,926

Representing Moving Images with Layers

by John Y.A. Wang, Edward H. Adelson , 1994
"... We describe a system for representing moving images with sets of overlapping layers. Each layer contains an intensity map that defines the additive values of each pixel, along with an alpha map that serves as a mask indicating the transparency. The layers are ordered in depth and they occlude each o ..."
Abstract - Cited by 542 (11 self) - Add to MetaCart
We describe a system for representing moving images with sets of overlapping layers. Each layer contains an intensity map that defines the additive values of each pixel, along with an alpha map that serves as a mask indicating the transparency. The layers are ordered in depth and they occlude each

Scalable Application Layer Multicast

by Suman Banerjee, Bobby Bhattacharjee, Christopher Kommareddy , 2002
"... We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data deliv ..."
Abstract - Cited by 719 (21 self) - Add to MetaCart
We describe a new scalable application-layer multicast protocol, specifically designed for low-bandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the application-layer multicast peers and can support a number of different data

Evolving Neural Networks through Augmenting Topologies

by Kenneth O. Stanley, Risto Miikkulainen - Evolutionary Computation
"... An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning task ..."
Abstract - Cited by 524 (113 self) - Add to MetaCart
An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning

Receiver-driven Layered Multicast

by Steven McCanne, Van Jacobson, Martin Vetterli , 1996
"... State of the art, real-time, rate-adaptive, multimedia applications adjust their transmission rate to match the available network capacity. Unfortunately, this source-based rate-adaptation performs poorly in a heterogeneous multicast environment because there is no single target rate — the conflicti ..."
Abstract - Cited by 749 (22 self) - Add to MetaCart
with a layered transmission system. By selectively forwarding subsets of layers at constrained network links, each user receives the best quality signal that the network can deliver. We and others have proposed that selective-forwarding be carried out using multiple IP-Multicast groups where each

Requirements for Internet Hosts - Communication Layers

by R. Braden - RFC1812] [RFC2277] Baker, F., "Requirements for IP Version 4 Routers", RFC 1812 , 1989
"... This RFC is an official specification for the Internet community. It incorporates by reference, amends, corrects, and supplements the primary protocol standards documents relating to hosts. Distribution of this document is unlimited. Summary This is one RFC of a pair that defines and discusses the r ..."
Abstract - Cited by 521 (6 self) - Add to MetaCart
the requirements for Internet host software. This RFC covers the communications protocol layers: link layer, IP layer, and transport layer; its companion RFC-1123 covers the application and support protocols.

Growing Cell Structures - A Self-organizing Network for Unsupervised and Supervised Learning

by Bernd Fritzke - Neural Networks , 1993
"... We present a new self-organizing neural network model having two variants. The first variant performs unsupervised learning and can be used for data visualization, clustering, and vector quantization. The main advantage over existing approaches, e.g., the Kohonen feature map, is the ability of the m ..."
Abstract - Cited by 301 (11 self) - Add to MetaCart
We present a new self-organizing neural network model having two variants. The first variant performs unsupervised learning and can be used for data visualization, clustering, and vector quantization. The main advantage over existing approaches, e.g., the Kohonen feature map, is the ability

Locally weighted learning

by Christopher G. Atkeson, Andrew W. Moore , Stefan Schaal - ARTIFICIAL INTELLIGENCE REVIEW , 1997
"... This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, ass ..."
Abstract - Cited by 594 (53 self) - Add to MetaCart
This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias

A Survey on Sensor Networks

by Lan F. Akyildiz, Welljan Su, Yogesh Sankarasubramaniam, Erdal Cayirci , 2002
"... Recent advancement in wireless communica- tions and electronics has enabled the develop- ment of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues that research ..."
Abstract - Cited by 1905 (1 self) - Add to MetaCart
Recent advancement in wireless communica- tions and electronics has enabled the develop- ment of low-cost sensor networks. The sensor networks can be used for various application areas (e.g., health, military, home). For different application areas, there are different technical issues

Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression

by John G. Daugman , 1988
"... Abstract-A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor ” representations for image analysis, segmentation, and compression. These transforms are conjoint spatiahpectral representations [lo], [15], which provide ..."
Abstract - Cited by 475 (8 self) - Add to MetaCart
Abstract-A three-layered neural network is described for transforming two-dimensional discrete signals into generalized nonorthogonal 2-D “Gabor ” representations for image analysis, segmentation, and compression. These transforms are conjoint spatiahpectral representations [lo], [15], which

Globally Consistent Range Scan Alignment for Environment Mapping

by F. Lu, E. Milios - AUTONOMOUS ROBOTS , 1997
"... A robot exploring an unknown environmentmay need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data is alig ..."
Abstract - Cited by 536 (8 self) - Add to MetaCart
A robot exploring an unknown environmentmay need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data
Results 1 - 10 of 437,926