Figure 1. Recurrent modular network architecture

A novel iterative approach based on a modular neural architecture [1] is presented for the classification of SAR images of sea ice. Additionally to the local image information the algorithm uses spatial context information derived from the first iteration of the algorithm and refines it in the subse...

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Bibliographic Details
Main Authors: Recurrent Modular Network, Andrey V. Bogdanov A, Marc Toussaint B, Stein S
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3173
http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf
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Summary:A novel iterative approach based on a modular neural architecture [1] is presented for the classification of SAR images of sea ice. Additionally 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 is used with the aim to capture structural features of the SAR images of sea ice in the Marginal Ice Zone.