Self-Organizing Maps for Automated Oil-Spill Detection

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Oleg Aulov

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.

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