International audienceThis paper presents CSOM, a Cellular Self-Organising Map which performs weight update in a cellular manner. Instead of updating weights towards new input vectors, it uses a signal propagation originated from the best matching unit to every other neuron in the network. Interactions between neurons are thus local and distributed. In this paper we present performance results showing than CSOM can obtain faster and better quantisation than classical SOM when used on high-dimensional vectors. We also present an application on video compression based on vector quantisation, in which CSOM outperforms SOM
The internet age has fuelled an enormous explosion in the amount of information generated by humanit...
Kohonen Self-Organizing maps are interesting computational structures because of their original prop...
In this paper, we introduce XPySom, a new open-source Python implementation of the well-known Self-O...
International audienceThis paper presents CSOM, a Cellular Self-Organising Map which performs weight...
International audienceSelf-organization is a bio-inspired feature that has been poorly develop...
Special Issue of the Neural Networks Journal after WSOM 05 in ParisNeural Networks Special Issue WSO...
International audienceSelf-organizing maps (SOM) are a well-known and biologically plausible model o...
A la suite de la conference ESANN 1999International audienceSelf-organizing maps (SOM) are widely us...
Mapping quality of the self-organising maps (SOMs) is sensitive to the map topology and initialisati...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
A new rate-constrained self-organising map (SOM) learning algorithm, incorporating a noise-mixing mo...
ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural networ...
Special issue of Neural Networks Journal after the WSOM 05 ConferenceSpecial issue of Neural Network...
In real world information systems, data analysis and processing are usually needed to be done in an ...
The internet age has fuelled an enormous explosion in the amount of information generated by humanit...
Kohonen Self-Organizing maps are interesting computational structures because of their original prop...
In this paper, we introduce XPySom, a new open-source Python implementation of the well-known Self-O...
International audienceThis paper presents CSOM, a Cellular Self-Organising Map which performs weight...
International audienceSelf-organization is a bio-inspired feature that has been poorly develop...
Special Issue of the Neural Networks Journal after WSOM 05 in ParisNeural Networks Special Issue WSO...
International audienceSelf-organizing maps (SOM) are a well-known and biologically plausible model o...
A la suite de la conference ESANN 1999International audienceSelf-organizing maps (SOM) are widely us...
Mapping quality of the self-organising maps (SOMs) is sensitive to the map topology and initialisati...
International audienceSelf-Organizing Maps (SOM) are well-known unsupervised neural networks able to...
A new rate-constrained self-organising map (SOM) learning algorithm, incorporating a noise-mixing mo...
ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural networ...
Special issue of Neural Networks Journal after the WSOM 05 ConferenceSpecial issue of Neural Network...
In real world information systems, data analysis and processing are usually needed to be done in an ...
The internet age has fuelled an enormous explosion in the amount of information generated by humanit...
Kohonen Self-Organizing maps are interesting computational structures because of their original prop...
In this paper, we introduce XPySom, a new open-source Python implementation of the well-known Self-O...