Paper Info
Title
Classification of multispectral remote-sensing images by neural networks
Abstract
This paper addresses the classification of multispectral remote-sensing images by the neural-network approach. In particular, an experimental comparison on the performances provided by different neural models for classifying multisensor remote-sensing data is reported. Four neural classifiers are considered in the comparison: the Multilayer Perceptron, Probabilistic Neural Networks, Radial Basis Function networks and a kind of Structured Neural Networks.
Year
Venue
Keywords
1996
Trieste, Italy
computer architecture,accuracy,remote sensing
Field
DocType
ISBN
Pattern recognition,Computer science,Multispectral image,Types of artificial neural networks,Time delay neural network,Multilayer perceptron,Artificial intelligence,Multispectral pattern recognition,Deep learning,Probabilistic logic,Artificial neural network
Conference
978-888-6179-83-6
Citations 
PageRank 
References 
2
0.40
11
Authors
4
Name
Order
Citations
PageRank
Fabio Roli14846311.69
Serpico, S.B.256048.52
Lorenzo Bruzzone34952387.72
Gianni Vernazza437850.89