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ICANN
2005
Springer
15 years 11 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
IJON
2006
123views more  IJON 2006»
15 years 6 months ago
Attractor neural networks with patchy connectivity
The neurons in the mammalian visual cortex are arranged in columnar structures, and the synaptic contacts of the pyramidal neurons in layer II/III are clustered into patches that ...
Christopher Johansson, Martin Rehn, Anders Lansner
IWANN
2005
Springer
15 years 11 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
ICANN
2003
Springer
15 years 11 months ago
Confidence Estimation Using the Incremental Learning Algorithm, Learn++
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
Jeffrey Byorick, Robi Polikar
IJON
2008
118views more  IJON 2008»
15 years 6 months ago
Incremental extreme learning machine with fully complex hidden nodes
Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879
Guang-Bin Huang, Ming-Bin Li, Lei Chen, Chee Kheon...