Abstract
Grid is a new technology. With corresponding middleware it can give strong computing power. In this paper we mainly discuss the middleware technology and architecture used in remote sensing image classification algorithm. Because unsupervised classification middleware is the key of the classification middleware algorithms, we study the alternant-unsupervised middleware and put forward a non-alternant unsupervised middleware scheme. Based on this scheme, main factors which effect the performance of non-alternant unsupervised classification are analyzed.
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Keywords
- Grid Node
- Computing Node
- Grid Environment
- Unsupervised Classification
- Laser Interferometer Gravitational Wave Observatory
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2004 Springer-Verlag Berlin Heidelberg
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Wang, J. et al. (2004). Preliminary Study on Unsupervised Classification of Remotely Sensed Images on the Grid. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3039. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25944-2_126
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DOI: https://doi.org/10.1007/978-3-540-25944-2_126
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22129-6
Online ISBN: 978-3-540-25944-2
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