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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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:
Sea ice
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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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.60.3173 2023-05-15T18:17:08+02:00 Figure 1. Recurrent modular network architecture Recurrent Modular Network Andrey V. Bogdanov A Marc Toussaint B Stein S The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3173 http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3173 http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf text ftciteseerx 2016-01-08T13:57:55Z 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. Text Sea ice Unknown
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description 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.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Recurrent Modular Network
Andrey V. Bogdanov A
Marc Toussaint B
Stein S
spellingShingle Recurrent Modular Network
Andrey V. Bogdanov A
Marc Toussaint B
Stein S
Figure 1. Recurrent modular network architecture
author_facet Recurrent Modular Network
Andrey V. Bogdanov A
Marc Toussaint B
Stein S
author_sort Recurrent Modular Network
title Figure 1. Recurrent modular network architecture
title_short Figure 1. Recurrent modular network architecture
title_full Figure 1. Recurrent modular network architecture
title_fullStr Figure 1. Recurrent modular network architecture
title_full_unstemmed Figure 1. Recurrent modular network architecture
title_sort figure 1. recurrent modular network architecture
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3173
http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf
genre Sea ice
genre_facet Sea ice
op_source http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.3173
http://www.marc-toussaint.net/publications/bogdanov-et-al-05.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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