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Proceedings Paper

Recurrent modular network architecture for sea ice classification in the marginal ice zone using ERS SAR images
Author(s): Andrey V. Bogdanov; Marc Toussaint; Stein Sandven
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Paper Abstract

A novel iterative approach based on a modular neural architecture (Jacobs, Jordan, and Barto, 1990) is presented for the classification of SAR images of sea ice. In addition to the local image information, the algorithm uses spatial context information derived from the first iteration of the algorithm and refines it in the subsequent iterations. The modular structure of the neural network aims to capture structural features of the SAR images of sea ice in the Marginal Ice Zone.

Paper Details

Date Published: 18 October 2005
PDF: 5 pages
Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 59820W (18 October 2005); doi: 10.1117/12.627776
Show Author Affiliations
Andrey V. Bogdanov, Ruhr-Univ. Bochum (Germany)
Marc Toussaint, Univ. of Edinburgh (United Kingdom)
Stein Sandven, Nansen Environmental and Remote Sensing Ctr. (Norway)

Published in SPIE Proceedings Vol. 5982:
Image and Signal Processing for Remote Sensing XI
Lorenzo Bruzzone, Editor(s)

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