A.G. Hatzimichailidis, G.A. Papakostas, V.G. Kaburlasos, “A distance measure based on fuzzy D-implications: application in pattern recognition”, British Journal of Mathematics & Computer Science, vol. 14, no. 3, pp. 1-14, 2016.
V.G. Kaburlasos, G.A. Papakostas, “Learning distributions of image features by interactive fuzzy lattice reasoning (FLR) in pattern recognition applications”, IEEE Computational Intelligence Magazine, vol. 10, no. 3, pp. 42–51, 2015 (Special Issue on New Trends of Learning in Computational Intelligence. Guest Editors: Guang-Bin Huang, Erik Cambria, Kar-Ann Toh, Bernard Widrow, Zongben Xu).
G.A. Papakostas, A. Savio, M. Graña, V.G. Kaburlasos, “A lattice computing approach to Alzheimer’s disease computer assisted diagnosis based on MRI data”, Neurocomputing, vol. 150, part A, pp. 37-42, 2015 (Special Issue on Bioinspired and knowledge based techniques and applications. Guest Editors: Manuel Graña and Bogdan Raducabu).
S.E. Papadakis, V.G. Kaburlasos, G.A. Papakostas, “Two fuzzy lattice reasoning (FLR) classifiers and their application for human facial expression recognition”, Journal of Multiple-Valued Logic and Soft Computing, vol. 22, no. 4-6, pp. 561-579, 2014 (Special Issue on Uncertainty Modeling in Knowledge Engineering and Decision Making. Guest Editors: Cengiz Kahraman and Farouk Yalaoui).
G.A. Papakostas, V.G. Kaburlasos, “Lattice Computing (LC) meta-representation for pattern classification”, Proceedings of the World Congress on Computational Intelligence (WCCI) 2014, FUZZ-IEEE Program, Beijing, China, 6-11 July 2014, pp. 39-44.
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