Recurrent modular network architecture for sea ice classification in the marginal ice zone using ERS SAR images

Andrey V. Bogdanov; Marc Toussaint; Stein Sandven

doi:10.1117/12.627776

Translator Disclaimer

18 October 2005 Recurrent modular network architecture for sea ice classification in the marginal ice zone using ERS SAR images

Andrey V. Bogdanov, Marc Toussaint, Stein Sandven

Author Affiliations +

Proceedings Volume 5982, Image and Signal Processing for Remote Sensing XI; 59820W (2005) https://doi.org/10.1117/12.627776
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

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.

Citation Download Citation

Andrey V. Bogdanov, Marc Toussaint, and Stein Sandven "Recurrent modular network architecture for sea ice classification in the marginal ice zone using ERS SAR images", Proc. SPIE 5982, Image and Signal Processing for Remote Sensing XI, 59820W (18 October 2005); https://doi.org/10.1117/12.627776

ACCESS THE FULL ARTICLE