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Staged training of Neocognitron by evolutionary algorithms
(Institute of Electrical and Electronics Engineers (IEEE), 1999)
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 ...
Molecular self-organisation in a developmental model for the evolution of large-scale artificial neural networks
(1998)
We argue that molecular self-organisation during embryonic development allows evolution to perform highly nonlinear combinatorial optimisation. A structured approach to architectural optimisation of large-scale Artificial ...
Evolution of developmental ontogeny for robustly reproducible phenotypes
(University of Hertfordshire, 1998)
Development has been used by a number of researchers as an efficient means of nonlinearly decoding genetic information is evolutionary systems. We show that developmental routines which do not utilise cell-cell interactions ...
Developmental evolution of an edge detecting retina
(Springer Nature, 1998)
Artificial evolution: modelling the development of the retina
(University of Hertfordshire, 1996)
The evolution of neural systems relies on the repeated modification of developmental programmes contained within genes. This paper proposes that to efficiently investigate artificial evolution, developmental processes must ...
Developmental artificial neural networks for shape recognition: a model of the retina
(University of Hertfordshire, 1996)
There has been recent interest in mimicking the self-organising processes of biological development to design artificial neural networks. An a priori decision must however be made as to the degree of biological detail ...