An unsupervised material learning method for imaging spectroscopy Jordan, Johannes, Angelopoulou, Elli and Robles-Kelly, Antonio 2014, An unsupervised material learning method for imaging spectroscopy, in IJCNN 2014 : Proceedings of the 2014 International Joint Conference on Neural Networks, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 2428-2435, doi: 10.1109/IJCNN.2014.6889441. Attached Files Name Description MIMEType Size Downloads Title An unsupervised material learning method for imaging spectroscopy Author(s) Jordan, Johannes Angelopoulou, Elli Robles-Kelly, Antonio orcid.org/0000-0002-2465-5971 Conference name International Neural Network Society. Conference (2014 : Beijing, China) Conference location Beijing, China Conference dates 2014/07/06 - 2014/07/11 Title of proceedings IJCNN 2014 : Proceedings of the 2014 International Joint Conference on Neural Networks Editor(s) [Unknown] Publication date 2014 Series International Neural Network Society Conference Start page 2428 End page 2435 Total pages 8 Publisher Institute of Electrical and Electronics Engineers Place of publication Piscataway, N.J. Keyword(s) Vectors Materials Equations Kernel Manifolds Prototypes Maximum likelihood estimation Science & Technology Technology Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Telecommunications Computer Science Engineering ISBN 978-1-4799-1484-5 Language eng DOI 10.1109/IJCNN.2014.6889441 Indigenous content off HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2014, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30123702 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 27 Jun 2019, 14:46:35 EST Thu, 27 Jun 2019, 15:55:43 EST Wed, 03 Jul 2019, 11:37:01 EST Thu, 04 Jul 2019, 06:03:26 EST Tue, 09 Jul 2019, 15:25:42 EST Tue, 09 Jul 2019, 15:27:11 EST Tue, 09 Jul 2019, 15:27:52 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 19 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Wed, 03 Jul 2019, 11:37:01 EST

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