Multiscale structures and algorithms that unify the treatment of local and global scene information are of particular importance in image segmentation. Vector quantization, owing to its versatility, has proved to be an effective means of image segmentation. Although vector quantization can be achieved using self-organizing maps with competitive learning, self-organizing maps in their original s...

A hybrid system which combines Self Organizing Maps and Case Based Reasoning is presented and apply to Structural Assessment. Self Organizing Maps are trained as a classification tool in order to organize the old cases in memory with the purpose of speeding up the Case Based Reasoning process. Three real structures have been used: An aluminium beam, a pipe section and a long pipe.

We propose a way of creating product maps with self-organizing maps (SOMs) for purchase decision making. We previously proposed a way of purchase decision support using SOMs and the Analytic Hierarchy Process (AHP). We provided several class boundaries, which divided the input features into several classes before creating self-organizing product maps. Because the number of classes and their bou...

Ant Colonies (or Swarm Intelligence) and Self-Organizing Maps (a type of unsupervised Neural Network) have become two important and powerful classification heuristics in computer science and artificial intelligence. After first describing each model, a hybrid is introduced that has the visual appeal of swarm intelligence and the efficiency of self-organizing maps.

Previously, we proposed an approach for corporate decision making with self-organizing patent maps labeled by technical terms and AHP. First, we extracted keywords by text mining to transform patent documents into feature vectors of the companies. Second, we inputted the feature matrix of technical terms and company names into self-organizing maps to create patent maps labeled by the technical ...