Vassilis G. Kaburlasos

Anestis G. Hatzimichailidis, George A. Papakostas, Vassilis G. Kaburlasos: A novel distance measure of intuitionistic fuzzy sets and its application to pattern recognition problems. Int. J. Intell. Syst. 27(4): 396-409 (2012)

Vassilis G. Kaburlasos, Stelios E. Papadakis, Angelos Amanatiadis: Binary Image 2D Shape Learning and Recognition Based on Lattice-Computing (LC) Techniques. Journal of Mathematical Imaging and Vision 42(2-3): 118-133 (2012)

Theodore P. Pachidis, Vassilis G. Kaburlasos: Person Identification Based on Lattice Computing k-Nearest-Neighbor Fingerprint Classification. KES 2012: 1720-1729

Vassilis G. Kaburlasos: Fuzzy Lattice Reasoning (FLR) Extensions to Lattice-Valued Logic. Panhellenic Conference on Informatics 2012: 445-448

Vassilis G. Kaburlasos: Special issue: Information engineering applications based on lattices. Inf. Sci. 181(10): 1771-1773 (2011)

Stelios E. Papadakis, Vassilis G. Kaburlasos: Piecewise-linear approximation of non-linear models based on probabilistically/possibilistically interpreted intervals' numbers (INs). Inf. Sci. 180(24): 5060-5076 (2010)

Vassilis G. Kaburlasos, Angelos Amanatiadis, Stelios E. Papadakis: 2-D Shape Representation and Recognition by Lattice Computing Techniques. HAIS (2) 2010: 391-398

Vassilis G. Kaburlasos: Granular Fuzzy Inference System (FIS) Design by Lattice Computing. HAIS (2) 2010: 410-417

Vassilis G. Kaburlasos, Stelios E. Papadakis: A granular extension of the fuzzy-ARTMAP (FAM) neural classifier based on fuzzy lattice reasoning (FLR). Neurocomputing 72(10-12): 2067-2078 (2009)

Vassilis G. Kaburlasos, Lefteris Moussiades, Athena Vakali: Fuzzy lattice reasoning (FLR) type neural computation for weighted graph partitioning. Neurocomputing 72(10-12): 2121-2133 (2009)

Vassilis G. Kaburlasos: Neural/Fuzzy Computing Based on Lattice Theory. Encyclopedia of Artificial Intelligence 2009: 1238-1243

Vassilis G. Kaburlasos, Catherine Marinagi, Vassilis Tsoukalas: Personalized multi-student improvement based on Bayesian cybernetics. Computers & Education 51(4): 1430-1449 (2008)

Vassilis G. Kaburlasos, Gerhard X. Ritter (Eds.): Computational Intelligence Based on Lattice Theory. Studies in Computational Intelligence 67, Springer 2007, isbn 978-3-540-72686-9

Vassilis G. Kaburlasos, Ioannis N. Athanasiadis, Pericles A. Mitkas: Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation. Int. J. Approx. Reasoning 45(1): 152-188 (2007)

Vassilis G. Kaburlasos, Athanasios Kehagias: Novel Fuzzy Inference System (FIS) Analysis and Design Based on Lattice Theory. IEEE T. Fuzzy Systems 15(2): 243-260 (2007)

Theodoros Alevizos, Vassilis G. Kaburlasos, Stelios E. Papadakis, Christos Skourlas, Petros Belsis: Fuzzy Interval Number (FIN) Techniques for Multilingual and Cross Language Information Retrieval. ICEIS (2) 2007: 348-355

Vassilis G. Kaburlasos: Unified Analysis and Design of ART/SOM Neural Networks and Fuzzy Inference Systems Based on Lattice Theory. IWANN 2007: 80-93

Vassilis G. Kaburlasos: Granular Enhancement of Fuzzy ART/SOM Neural Classifiers Based on Lattice Theory. Computational Intelligence Based on Lattice Theory 2007: 3-23

Vassilis G. Kaburlasos, Stelios E. Papadakis: Granular self-organizing map (grSOM) for structure identification. Neural Networks 19(5): 623-643 (2006)

Catherine Marinagi, Theodoros Alevizos, Vassilis G. Kaburlasos, Christos Skourlas: Fuzzy Interval Number (FIN) Techniques for Cross Language Information Retrieval. ICEIS (2) 2006: 249-256

Stelios E. Papadakis, Panagiotis Tzionas, Vassilis G. Kaburlasos, John B. Theocharis: A Genetic Based Approach to the Type I Structure Identification Problem. Informatica, Lith. Acad. Sci. 16(3): 365-382 (2005)

Vassilis G. Kaburlasos: FINs: lattice theoretic tools for improving prediction of sugar production from populations of measurements. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(2): 1017-1030 (2004)

Vassilis G. Kaburlasos, Catherine Marinagi, Vassilis Tsoukalas: PARES: A Software Tool for Computer-Based Testing and Evaluation Used in the Greek Higher Education System. ICALT 2004: 0-

Athanasios Kehagias, Vassilios Petridis, Vassilis G. Kaburlasos, Pavlina Fragkou: A Comparison of Word- and Sense-Based Text Categorization Using Several Classification Algorithms. J. Intell. Inf. Syst. 21(3): 227-247 (2003)

Vassilios Petridis, Vassilis G. Kaburlasos: FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples. Journal of Machine Learning Research 4: 17-37 (2003)

Al Cripps, Vassilis G. Kaburlasos, Nghiep Nguyen, Stelios E. Papadakis: Improved Experimental Results Using Fuzzy Lattice Neurocomputing (FLN) Classifiers. MLMTA 2003: 161-166

Vassilis G. Kaburlasos, V. A. Spais, Vassilios Petridis, Loukas Petrou, Spiridon A. Kazarlis, N. Maslaris, A. Kallinakis: Intelligent clustering techniques for prediction of sugar production. Mathematics and Computers in Simulation 60(3-5): 159-168 (2002)

Vassilios Petridis, Vassilis G. Kaburlasos: Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN). IEEE Trans. Knowl. Data Eng. 13(2): 245-260 (2001)

Vassilis G. Kaburlasos, Vassilios Petridis: Fuzzy Lattice Neurocomputing (FLN) models. Neural Networks 13(10): 1145-1170 (2000)

Vassilios Petridis, Vassilis G. Kaburlasos: Learning in the framework of fuzzy lattices. IEEE T. Fuzzy Systems 7(4): 422-440 (1999)

Vassilis G. Kaburlasos, Vassilios Petridis, Peter N. Brett, Dave A. Baker: Estimation of the stapes-bone thickness in the stapedotomy surgical procedure using a machine-learning technique. IEEE Transactions on Information Technology in Biomedicine 3(4): 268-277 (1999)

Vassilios Petridis, Vassilis G. Kaburlasos: Fuzzy lattice neural network (FLNN): a hybrid model for learning. IEEE Transactions on Neural Networks 9(5): 877-890 (1998)

Vassilis G. Kaburlasos, Vassilios Petridis, Peter N. Brett, Dave A. Baker: Learning a Linear Association of Drilling Profiles in Stapedotomy Surgery. ICRA 1998: 705-710

Dwight D. Egbert, Philip H. Goodman, Vassilis G. Kaburlasos, John H. Witchey: Generalization Capabilities of Subtle Image Pattern Classifiers. IEEE Trans. Knowl. Data Eng. 4(2): 172-177 (1992)

Dwight D. Egbert, Vassilis G. Kaburlasos, Philip H. Goodman: Invariant feature extraction for neurocomputer analysis of biomedical images. CBMS 1989: 69-73