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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 ...
Human shape recognition from snakes using neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 1999)
This paper documents experiments which have been carried out with several neural network systems designed to categorise pedestrian shapes from non-pedestrian shapes. Active Contour models (‘Snakes’) [1] have been used to ...
Detecting partial occlusion of humans using snakes and neural networks
(1999)
This paper summarises the development of a computer system designed to detect moving humans in an image or series of images. The system combines the use of active contour models, ‘snakes’, which detect human objects in an ...
Developmental evolution of dendritic morphology in a multi-compartmental neuron model
(IEE, 1999)
Through the use of a multi-compartmental neuron simulation, Mainen and Sejnowski demonstrated that spike generation in neurons is a function of their dendritic structure [l]. In this paper we investigate the determination ...
Hierarchical Classification with a Competitive Evolutionary Neural Tree
(1999)
A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT ...