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Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC
(Joint)		 2018-03-14
10:00		 Tokyo Kikai-Shinko-Kaikan Bldg. Hierarchical quaternion neural networks with self-organizing codebook for unsupervised PolSAR land classification
Hyunsoo Kim, Akira Hirose (Tokyo Univ.) NC2017-88		 We propose a self-organizing codebook-based hierarchical polarization feature vector generation to realize an unsupervis... [more] NC2017-88
pp.121-126
EMT, IEE-EMT 2017-11-09
10:50		 Yamagata Tendo Hotel (Tendo, Yamagata) Flexible Unsupervised PolSAR Land Classification System Based on Quaternion Neural Networks
Hyunsoo Kim, Akira Hirose (Tokyo Univ.) EMT2017-48		 We propose a flexible unsupervised PolSAR land classification system based on quaternion neural networks. The existing ... [more] EMT2017-48
pp.37-42
SANE 2017-10-05
14:20		 Tokyo Maison franco - japonaise (Tokyo) Unsupervised Adaptive PolSAR Land Classification System Using Quaternion Neural Networks
Hyunsoo Kim, Akira Hirose (Univ. of Tokyo) SANE2017-57		 We propose an unsupervised adaptive PolSAR land classification system using quaternion neural networks. Most of the exis... [more] SANE2017-57
pp.73-78
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