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ICANN
2007
Springer
15 years 5 months ago
Multi-dimensional Recurrent Neural Networks
Abstract. Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properti...
Alex Graves, Santiago Fernández, Jürge...
GECCO
2004
Springer
212views Optimization» more  GECCO 2004»
15 years 4 months ago
An Evolutionary Autonomous Agent with Visual Cortex and Recurrent Spiking Columnar Neural Network
Spiking neural networks are computationally more powerful than conventional artificial neural networks. Although this fact should make them especially desirable for use in evoluti...
Rich Drewes, James B. Maciokas, Sushil J. Louis, P...
116
Voted
JOCN
2010
117views more  JOCN 2010»
14 years 5 months ago
The Neural Substrates and Timing of Top-Down Processes during Coarse-to-Fine Categorization of Visual Scenes: A Combined fMRI an
Spatial frequencies in an image influence visual analysis across a distributed, hierarchically organized brain network. Low spatial frequency (LSF) information may rapidly reach h...
Carole Peyrin, Christoph M. Michel, Sophie Schwart...
101
Voted
ICIP
1998
IEEE
16 years 18 days ago
A Neural Network Approach for Reconstructing Surface Shape from Shading
In this work, a framework for the reconstruction of smooth surface shapes from shading images is presented. The method is based on using a backpropagationbased neural network for ...
Jezekiel Ben-Arie, Dibyendu Nandy
ICCV
2007
IEEE
16 years 1 months ago
Supervised Learning of Image Restoration with Convolutional Networks
Convolutional networks have achieved a great deal of success in high-level vision problems such as object recognition. Here we show that they can also be used as a general method ...
Viren Jain, Joseph F. Murray, Fabian Roth, Sriniva...