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Deep rectifier networks

University of Montreal / Université de MontréalImage classification

Deep rectifier networks is image classification model published by University of Montreal / Université de Montréal in 2011.

About Deep rectifier networks

While logistic sigmoid neurons are more biologically plausible than hyperbolic tangent neurons, the latter work better for training multi-layer neural networks. This paper shows that rectifying neurons are an even better model of biological neurons a

Details

Provider
University of Montreal / Université de Montréal
Task
Image classification
Released
2011-04-13
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