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% KERNEL MANIFOLD ALIGNMENT
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% This demo illustrates the performance of the semisupervised kernel % manifold alignment (KEMA) in several toy examples.
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% All these programs included in this package are intended for illustration
% purposes and as accompanying software for the paper:
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% Devis Tuia and Gustau Camps-Valls. % "Kernel Manifold Alignment for Domain Adaptation". PLoS One, 2016
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% If you find the software useful in other domains, we would greatly % acknowledge % citing our paper above. Also, please consider citing these papers:
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% Semisupervised Manifold Alignment of Multimodal Remote Sensing Images
% Devis Tuia, Michele Volpi, Maxime Trolliet, and G. Camps-Valls
% IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7708-7720, Dec. 2014
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% Unsupervised Alignment of Image Manifolds with Centrality Measures
% Devis Tuia, Michele Volpi and G. Camps-Valls
% 22nd International Conference on Pattern Recognition, ICPR 2014
% Stockholm, Sweden, August 2014
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% Copyright & Disclaimer
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%
% The programs contained in this package are granted free of charge for
% research and education purposes only. Scientific results produced using
% the software provided shall acknowledge the use of this implementation
% provided by us. If you plan to use it for non-scientific purposes,
% don't hesitate to contact us. Because the programs are licensed free of
% charge, there is no warranty for the program, to the extent permitted
% by applicable law. except when otherwise stated in writing the
% copyright holders and/or other parties provide the program "as is"
% without warranty of any kind, either expressed or implied, including,
% but not limited to, the implied warranties of merchantability and
% fitness for a particular purpose. the entire risk as to the quality and
% performance of the program is with you. should the program prove
% defective, you assume the cost of all necessary servicing, repair or
% correction. In no event unless required by applicable law or agreed to
% in writing will any copyright holder, or any other party who may modify
% and/or redistribute the program, be liable to you for damages,
% including any general, special, incidental or consequential damages
% arising out of the use or inability to use the program (including but
% not limited to loss of data or data being rendered inaccurate or losses
% sustained by you or third parties or a failure of the program to
% operate with any other programs), even if such holder or other party
% has been advised of the possibility of such damages.
%
% NOTE: This is just a demo providing a default initialization. Training
% is not at all optimized. Other initializations, optimization techniques, % and training strategies may be of course better suited to achieve improved % results in this or other problems. We just did it in the standard way for % illustration purposes and dissemination of these models. %
% Copyright (c) 2015 by Devis Tuia and Gustau Camps-Valls
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% Devis Tuia, <devis.tuia@geo.uzh.ch> % University of Zurich, Switzerland % http://www.geo.uzh.ch/en/units/multimodal-remote-sensing
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% Gustau Camps-Valls, <gustau.camps@uv.es>, % Universitat de Valencia, Spain
% http://isp.uv.es/
%