An unsupervised neural network based on a new neural unit is applied to the problem of clustering a data set of pixels drawn through remote sensing of a limited portion of the terrestrial surface. The aim of the partition is to split the sensed area into sets having roughly the same type of ground cover. After the partitioning a comparison with the ground truth has shown that the unsupervised net has been able to split accurately the given data set in subsets similar to the classes really observable with a fast convergence and a high resolution.
|Titolo:||Clustering in Remote Sensing Using an Unsupervised Neural Network|
|Data di pubblicazione:||1996|
|Nome del convegno:||8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications, MELECON '96|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1109/MELCON.1996.551221|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|