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NECO
2008
114views more  NECO 2008»
15 years 5 months ago
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
Cornelius Weber, Jochen Triesch
FGCS
2007
89views more  FGCS 2007»
15 years 4 months ago
Federated grid clusters using service address routed optical networks
Clusters of computers have emerged as cost-effective parallel and/or distributed computing systems for computationally intensive tasks. Normally, clusters are composed of high per...
Isaac D. Scherson, Daniel S. Valencia, Enrique Cau...
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 4 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
RAS
2006
86views more  RAS 2006»
15 years 4 months ago
Using cellular automata and gradients to control self-reconfiguration
Self-reconfigurable robots are built from modules, which are autonomously able to change the way they are connected. Such a robot can, through this self-reconfiguration process, c...
Kasper Støy
IJCM
2007
205views more  IJCM 2007»
15 years 4 months ago
BTF modelling using BRDF texels
The highest fidelity representations of realistic real-world materials currently used comprise Bidirectional Texture Functions (BTF). The BTF is a six dimensional function dependi...
Jirí Filip, Michal Haindl