Self-Organizing Maps for Automated Oil-Spill Detection
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Revision as of 08:35, December 28, 2011 by Carolbmeyer (talk | contribs) (Created page with "A self-organizing map (SOM) or selforganizing feature map (SOFM) is a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (...")
A self-organizing map (SOM) or selforganizing feature map (SOFM) is a type of artificial neural network that is trained using unsupervised learning to produce a low-dimensional (typically twodimensional), discretized representation of the input space of the training samples, called a map. Self-organizing maps are different from other artificial neural networks in the sense that they use a neighborhood function to preserve the topological properties of the input space.
