Chapter title | Object representation with self-organising networks |
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Authors | Angelopoulou, A., Psarrou, A. and García Rodríguez, J. |
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Editors | Cabestany, J., Rojas, I. and Joya, G. |
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Abstract | This paper, aims to address the ability of self-organising networks to automatically extract and correspond landmark points using only topological relations derived from competitive hebbian learning. We discuss, how the Growing Neural Gas (GNG) algorithm can be used for the automatic extraction and correspondence of nodes in a set of objects, which are then used to built statistical human brain MRI and hand gesture models. |
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Book title | Advances in computational intelligence: 11th international work-conference on artificial neural networks, IWANN 2011, Torremolinos-Malaga, Spain, June 8-10, 2011 |
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Page range | 244-251 |
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Year | 2011 |
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Publisher | Springer |
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Publication dates |
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Published | 2011 |
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Series | Lecture Notes in Computer Science |
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ISBN | 9783642214974 |
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ISSN | 0302-9743 |
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Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-642-21498-1_31 |
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Web address (URL) | http://www.scopus.com/inward/record.url?eid=2-s2.0-79957930585&partnerID=MN8TOARS |
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Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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