Abstract — 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.
Part 3: Classification - Pattern RecognitionInternational audienceColor image processing systems are...
Abstract. Catastrophic Interference is a well known problem of Artifi-cial Neural Networks (ANN) lea...
Color quantization (CQ) is an image processing task popularly used to convert true color images to p...
A new self-organizing map with variable topology is introduced for image segmentation. The proposed ...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
Self-organising? feature maps (SOFM) are an important tool to visualize high-dimensional data as a t...
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...
Neste trabalho apresentamos um novo modelo neural para segmentação de imagens, baseado nos Mapas Au...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
An algorithm for the topological segmentation of high dimensional data is pro-posed. The algorithm c...
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
Self-organizing map has been applied to a variety of tasks including data visualization and clusteri...
Abstract- Se1f-organizing feature maps (SOFM) are an important tool to visualize high-dimensional da...
Boundary extraction for object region segmentation is one of the most challenging tasks in image pro...
Part 3: Classification - Pattern RecognitionInternational audienceColor image processing systems are...
Abstract. Catastrophic Interference is a well known problem of Artifi-cial Neural Networks (ANN) lea...
Color quantization (CQ) is an image processing task popularly used to convert true color images to p...
A new self-organizing map with variable topology is introduced for image segmentation. The proposed ...
We propose a new competitive-learning neural network model for colour image segmentation. The model,...
Self-organising? feature maps (SOFM) are an important tool to visualize high-dimensional data as a t...
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...
Neste trabalho apresentamos um novo modelo neural para segmentação de imagens, baseado nos Mapas Au...
Artificial neural networks have gained a lot of interest as empirical models for their powerful repr...
An algorithm for the topological segmentation of high dimensional data is pro-posed. The algorithm c...
[[abstract]]© 1999 World Scientific and Engineering Academy and Society-In this paper, a color segme...
Self-organizing map has been applied to a variety of tasks including data visualization and clusteri...
Abstract- Se1f-organizing feature maps (SOFM) are an important tool to visualize high-dimensional da...
Boundary extraction for object region segmentation is one of the most challenging tasks in image pro...
Part 3: Classification - Pattern RecognitionInternational audienceColor image processing systems are...
Abstract. Catastrophic Interference is a well known problem of Artifi-cial Neural Networks (ANN) lea...
Color quantization (CQ) is an image processing task popularly used to convert true color images to p...