Results 1 - 10 of 35,627

A Model of Saliency-based Visual Attention for Rapid Scene Analysis

by Laurent Itti, Christof Koch, Ernst Niebur , 1998
"... A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing salie ..."
Abstract - Cited by 1748 (72 self) - Add to MetaCart
A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing

Alliances and networks

by Ranjay Gulati
"... This paper introduces a social network perspective to the study of strategic alliances. It extends prior research, which has primarily considered alliances as dyadic exchanges and paid less attention to the fact that key precursors, processes, and outcomes associated with alliances can be defined an ..."
Abstract - Cited by 833 (6 self) - Add to MetaCart
This paper introduces a social network perspective to the study of strategic alliances. It extends prior research, which has primarily considered alliances as dyadic exchanges and paid less attention to the fact that key precursors, processes, and outcomes associated with alliances can be defined

Data networks

by L. Verger G, E. Gros D'aillon G, P. Major H, G. Németh H , 1992
"... a b s t r a c t In this paper we illustrate the core technologies at the basis of the European SPADnet project (www. spadnet.eu), and present the corresponding first results. SPADnet is aimed at a new generation of MRI-compatible, scalable large area image sensors, based on CMOS technology, that are ..."
Abstract - Cited by 2210 (5 self) - Add to MetaCart
a b s t r a c t In this paper we illustrate the core technologies at the basis of the European SPADnet project (www. spadnet.eu), and present the corresponding first results. SPADnet is aimed at a new generation of MRI-compatible, scalable large area image sensors, based on CMOS technology

Neural Network-Based Face Detection

by Henry A. Rowley, Shumeet Baluja, Takeo Kanade - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1998
"... We present a neural network-based upright frontal face detection system. A retinally connected neural network examines small windows of an image and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We present ..."
Abstract - Cited by 1206 (22 self) - Add to MetaCart
We present a neural network-based upright frontal face detection system. A retinally connected neural network examines small windows of an image and decides whether each window contains a face. The system arbitrates between multiple networks to improve performance over a single network. We present

The EigenTrust Algorithm for Reputation Management in P2P Networks

by Sepandar D. Kamvar, Mario T. Schlosser, Hector Garcia-molina - in Proceedings of the 12th International World Wide Web Conference (WWW 2003 , 2003
"... Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience with P2P networks such as Gnutella shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread of self ..."
Abstract - Cited by 997 (23 self) - Add to MetaCart
Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience with P2P networks such as Gnutella shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread

Imagenet classification with deep convolutional neural networks.

by Alex Krizhevsky , Ilya Sutskever , Geoffrey E Hinton - In Advances in the Neural Information Processing System, , 2012
"... Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the pr ..."
Abstract - Cited by 1010 (11 self) - Add to MetaCart
Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than

A Learning Algorithm for Continually Running Fully Recurrent Neural Networks

by Ronald J. Williams, David Zipser , 1989
"... The exact form of a gradient-following learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a precis ..."
Abstract - Cited by 534 (4 self) - Add to MetaCart
the retention of information over time periods having either fixed or indefinite length. 1 Introduction A major problem in connectionist theory is to develop learning algorithms that can tap the full computational power of neural networks. Much progress has been made with feedforward networks, and attention

Analysis of TCP Performance over Mobile Ad Hoc Networks Part I: Problem Discussion and Analysis of Results

by Gavin Holland, Nitin Vaidya , 1999
"... Mobile ad hoc networks have gained a lot of attention lately as a means of providing continuous network connectivity to mobile computing devices regardless of physical location. Recently, a large amount of research has focused on the routing protocols needed in such an environment. In this two-part ..."
Abstract - Cited by 521 (5 self) - Add to MetaCart
Mobile ad hoc networks have gained a lot of attention lately as a means of providing continuous network connectivity to mobile computing devices regardless of physical location. Recently, a large amount of research has focused on the routing protocols needed in such an environment. In this two

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

by John G. Daugman , 1988
"... 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 spatial/spectral representations [lo], [15], which provide a comp ..."
Abstract - Cited by 478 (8 self) - Add to MetaCart
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 spatial/spectral representations [lo], [15], which provide a

Learning low-level vision

by William T. Freeman, Egon C. Pasztor - International Journal of Computer Vision , 2000
"... We show a learning-based method for low-level vision problems. We set-up a Markov network of patches of the image and the underlying scene. A factorization approximation allows us to easily learn the parameters of the Markov network from synthetic examples of image/scene pairs, and to e ciently prop ..."
Abstract - Cited by 579 (30 self) - Add to MetaCart
We show a learning-based method for low-level vision problems. We set-up a Markov network of patches of the image and the underlying scene. A factorization approximation allows us to easily learn the parameters of the Markov network from synthetic examples of image/scene pairs, and to e ciently
Results 1 - 10 of 35,627