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IEEEICCI
2007
IEEE
14 years 1 months ago
An Image Association Model of the Brodmann Areas
The ability to associate images is the basis for learning relationships involving vision, hearing, tactile sensation, and kinetic motion. A new architecture is described that has ...
Douglas S. Greer
ICANN
2010
Springer
13 years 8 months ago
Using Reinforcement Learning to Guide the Development of Self-organised Feature Maps for Visual Orienting
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...
Kevin Brohan, Kevin N. Gurney, Piotr Dudek
MS
2003
13 years 9 months ago
Information-theoretic Competitive Learning
— In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors bet...
Ryotaro Kamimura
FLAIRS
2008
13 years 10 months ago
The Introspective Robot: Using Self-Prediction to Improve Robot Learning
We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
IROS
2007
IEEE
179views Robotics» more  IROS 2007»
14 years 1 months ago
Incremental learning for place recognition in dynamic environments
Abstract— Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be ...
Jie Luo, Andrzej Pronobis, Barbara Caputo, Patric ...