Abstract
We propose a ground penetrating radar system to integrate mutimodal information of space- and frequency- domain textural features in self-organization that is modulated by mutual information. We use the MuSOM (mutual-information-based self-organizing map) architecture we proposed previously, in which the mutual information among the data fed to multiple SOMs modulates the SOM dynamics. Experiments demonstrate that our system makes meaningful clusters of landmine features clearer than a conventional non-MuSOM system does.
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References
Sato, M., Fujiwara, J., Fenga, X., Kobayashi, T.: Dual sensor ALIS evaluation test in Afghanistan. IEEE Geoscience and Remote Sensing Society Newsletter, 22–27 (Septermber 2005)
Hara, T., Hirose, A.: Plastic mine detecting system using complex-valued self-organizing map that deals with multiple-frequency interferometric images. Neural Networks 17(8-9), 1201–1210 (2004)
Masuyama, S., Hirose, A.: Walled LTSA array for rapid, high spatial resolution, and phase sensitive imaging to visualize plastic landmines. IEEE Transactions on Geoscience and Remote Sensing 45(8), 2536–2543 (2007)
Masuyama, S., Yasuda, K., Hirose, A.: Multiple mode selection of walled-ltsa array elements for high resolution imaging to visualize antipersonnel plastic landmines. IEEE Geoscience and Remote Sensing Letters 5(4), 745–749 (2008)
Nakano, Y., Hirose, A.: Improvement of plastic landmine visualization performance by use of ring-CSOM and frequency-domain local correlation. IEICE Transactions on Electronics E92-C(1), 102–108 (2009)
Kitahara, K., Hirose, A.: A concept generation method based on mutual information quantity among multiple self-organizing maps. In: Proceedings of the International Conference on Neural Inform. Processing (ICONIP) 2009 Bangkok, pp. 263–272 (2009)
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Hirose, A., Ejiri, A., Kitahara, K. (2010). Ground Penetrating Radar System with Integration of Mutimodal Information Based on Mutual Information among Multiple Self-Organizing Maps. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_51
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DOI: https://doi.org/10.1007/978-3-642-17534-3_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17533-6
Online ISBN: 978-3-642-17534-3
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