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        Staged training of Neocognitron by evolutionary algorithms

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        901702.pdf (PDF, 734Kb)
        Author
        Pan, Z.
        Sabisch, T.
        Adams, R.G.
        Bolouri, H.
        Attention
        2299/1569
        Abstract
        The Neocognitron, inspired by the mammalian visual system, is a complex neural network with numerous parameters and weights which should be trained in order to utilise it for pattern recognition. However, it is not easy to optimise these parameters and weights by gradient decent algorithms. In this paper, we present a staged training approach using evolutionary algorithms. The experiments demonstrate that evolutionary algorithms can successfully train the Neocognitron to perform image recognition on real world problems.
        Publication date
        1999
        Published in
        In: Procs of the 1999 Congress on Evolutionary Computation (CEC'99) Vol. 3
        Published version
        https://doi.org/10.1109/CEC.1999.785515
        Other links
        http://hdl.handle.net/2299/1569
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