Sciweavers

29
Voted
PRIS
2004

Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features

14 years 10 days ago
Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features
Abstract. This paper treats on rotation absorption in neural networks for multioriented character recognition. Classical approaches are based on several rotation invariant features. Here, we propose to use a dynamic neural network topology to absorb the rotation phenomenon. The basic idea is to preserve as most as possible the graphical information, that contains all the information. The proposal is to dynamically modify the neural network architecture, in order to take into account the rotation variation of the analysed pattern. We use too a specific topology that carry out a polar transformation inside the network. The interest of such a transformation is to transform the rotation problem from a
Christophe Choisy, Hubert Cecotti, Abdel Belaï
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where PRIS
Authors Christophe Choisy, Hubert Cecotti, Abdel Belaïd
Comments (0)