A new self-organizing map with variable topology is introduced for image segmentation. The proposed network, called Local Adaptive Receptive Field Self-Organizing Map (LARFSOM-RBF), is a two-stage network capable of both color and border segment images. The color segmentation stage is responsibility of LARFSOM which is characterized by adaptive number of nodes, fast convergence and variable topology. For border segmentation RBF nodes are included to determine the border pixels using previously learned information of LARFSOM. LARFSOM-RBF was tested to segment images with different degrees of complexity showing promising results
Introduction Competing neurons are able to create spatial filters of circular shape and of equal siz...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space...
Self-organizing map has been applied to a variety of tasks including data visualization and clusteri...
A new self-organizing map with variable topology is introduced for image segmentation. The proposed ...
Abstract — A new self-organizing map with variable topology is introduced for image segmentation. Th...
We propose a two-stage hierarchical artificial neural network for the segmentation of color images b...
Abstract:- In this paper, a color segmentation algorithm is presented and the parameters are discuss...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
Boundary extraction for object region segmentation is one of the most challenging tasks in image pro...
Image segmentation is an essential step in image processing. Many image segmentation methods are ava...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
Image segmentation is an essential step in image processing. Many image segmentation methods are ava...
The paper describes a self supervised parallel self organizing neural network (PSONN) architecture f...
Image segmentation means separation process that can divide the original image into smaller area wit...
Introduction Competing neurons are able to create spatial filters of circular shape and of equal siz...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space...
Self-organizing map has been applied to a variety of tasks including data visualization and clusteri...
A new self-organizing map with variable topology is introduced for image segmentation. The proposed ...
Abstract — A new self-organizing map with variable topology is introduced for image segmentation. Th...
We propose a two-stage hierarchical artificial neural network for the segmentation of color images b...
Abstract:- In this paper, a color segmentation algorithm is presented and the parameters are discuss...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
Boundary extraction for object region segmentation is one of the most challenging tasks in image pro...
Image segmentation is an essential step in image processing. Many image segmentation methods are ava...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
Image segmentation is an essential step in image processing. Many image segmentation methods are ava...
The paper describes a self supervised parallel self organizing neural network (PSONN) architecture f...
Image segmentation means separation process that can divide the original image into smaller area wit...
Introduction Competing neurons are able to create spatial filters of circular shape and of equal siz...
Usually, the segmentation of color images is performed using cluster-based methods and the RGB space...
Self-organizing map has been applied to a variety of tasks including data visualization and clusteri...