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147
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BC
2006
149views more  BC 2006»
15 years 4 months ago
Learning invariant object recognition in the visual system with continuous transformations
Abstract The cerebral cortex utilizes spatiotemporal continuity in the world to help build invariant representations. In vision, these might be representations of objects. The temp...
Simon M. Stringer, G. Perry, Edmund T. Rolls, J. H...
BMCBI
2004
120views more  BMCBI 2004»
15 years 3 months ago
Clustering under the line graph transformation: application to reaction network
Background: Many real networks can be understood as two complementary networks with two kind of nodes. This is the case of metabolic networks where the first network has chemical ...
Jose C. Nacher, Nobuhisa Ueda, Takuji Yamada, Mino...
153
Voted
JMLR
2012
13 years 6 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
EGOV
2008
Springer
15 years 5 months ago
Paving the Way to eGovernment Transformation: Interoperability Registry Infrastructure Development
During the last decades eGovernment has been a vivid, dynamic research and development area. As services are being transformed, electronic documents and web services appear every d...
Aikaterini-Maria Sourouni, Fenareti Lampathaki, Sp...
CVPR
2010
IEEE
15 years 5 months ago
The Phase Only Transform for unsupervised surface defect detection
We present a simple, fast, and effective method to detect defects on textured surfaces. Our method is unsupervised and contains no learning stage or information on the texture bei...
Dror Aiger, Hugues Talbot