Extreme Learning Classifier With Deep Concepts



The text below describes a short introduction to extreme learning machines (ELM) enlightened by new developed applications. It also includes an introduction to deep belief networks (DBN), slightly tuned in the pattern recognition problems. Essentially, the deep belief networks learn to extract invariant characteristics of an object, or, in other words, a DBN shows the ability to simulate how the brain recognizes patterns by the contrastive divergence algorithm and choosing a particular network configuration. Finally, it contains a strategy based on the extreme learning of the deep features, enhancing the recognition rate within the ELM approach, and concluding with successful experimental results in well-known benchmarks.


Extreme Learning Machines, Restricted Boltzmann Machines, Deep Belief Networks, Deep learning


18th Iberoamerican Congress on Pattern Recognition (CIARP 2013), LNCS; Springer, November 2013

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Year 2016 : 1 citations

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Year 2015 : 3 citations

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Year 2014 : 2 citations

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