Paper Info
Title
Investigation of Entropy Nets Induced by Oblique Decision Trees for Target Detection in Ocean SAR.
Abstract
An artificial neural network whose topology is informed by an Oblique Decision Tree is applied to target detection in maritime Synthetic Aperture Radar. The number of neurons in the first layer is the same as the number of decision tree nodes and the number of nodes in the second hidden layer is the same as the number of leaf nodes. The neural network output are the class labels. Our approach differs from other efforts in the literature in that the Oblique Decision Tree and the Fisher's Linear Discriminant are used as a decision criterion. Classifier testing and validation were achieved, applying these algorithms to radar images. Initial results are practical with satisfactory training time; generalization capability and a speedy architecture definition.
Year
DOI
Venue
2012
10.1007/978-3-642-32692-9_17
Communications in Computer and Information Science
Keywords
Field
DocType
artificial neural networks,decision trees,SAR,target detection,remote sensing,entropy nets
Decision tree,Oblique case,Radar imaging,Pattern recognition,Synthetic aperture radar,Computer science,Artificial intelligence,Linear discriminant analysis,Artificial neural network,Decision tree learning,Incremental decision tree
Conference
Volume
ISSN
Citations 
310
1865-0929
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Rafael L. Paes101.69
Ivo P. Medeiros281.00