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Roger Trias-Sanz and Nicolas Lom{\'e}nie
ABSTRACT
A set of methodologies and techniques for automatic detection of bridges in pan-chromatic, high-resolution satellite images is presented. These methods rely on (a) radiometric features and neural networks to classify each pixel into several terrain types, and (b) fixed rules to find bridges in this classification. They can be easily extended to other kinds of geographical objects, and integrated with existing techniques using geometric features. The proposed method has been tested in a number of experiments. 
ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Automatic Bridge Detection in High-Resolution Satellite Images Site generated on Friday, 06 January 2006