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.
Clustering in Remote Sensing Using an Unsupervised Neural Network / Acciani, G.; Chiarantoni, E.. - STAMPA. - (1996), pp. 1446-1448. (Intervento presentato al convegno 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications, MELECON '96 tenutosi a Bari, Italy nel May 13-16, 1996) [10.1109/MELCON.1996.551221].
Clustering in Remote Sensing Using an Unsupervised Neural Network
G. Acciani;E. Chiarantoni
1996-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
