Vassilis G. Kaburlasos Vis

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23EEVassilis 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)
22EEVassilis G. Kaburlasos, Lefteris Moussiades, Athena Vakali: Fuzzy lattice reasoning (FLR) type neural computation for weighted graph partitioning. Neurocomputing 72(10-12): 2121-2133 (2009)
21EEVassilis G. Kaburlasos, Catherine Marinagi, Vassilis Tsoukalas: Personalized multi-student improvement based on Bayesian cybernetics. Computers & Education 51(4): 1430-1449 (2008)
20 Vassilis G. Kaburlasos, Gerhard X. Ritter: Computational Intelligence Based on Lattice Theory Springer 2007
19 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
18EEVassilis G. Kaburlasos: Unified Analysis and Design of ART/SOM Neural Networks and Fuzzy Inference Systems Based on Lattice Theory. IWANN 2007: 80-93
17EEVassilis G. Kaburlasos: Granular Enhancement of Fuzzy ART/SOM Neural Classifiers Based on Lattice Theory. Computational Intelligence Based on Lattice Theory 2007: 3-23
16EEVassilis 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)
15EEVassilis 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)
14 Catherine Marinagi, Theodoros Alevizos, Vassilis G. Kaburlasos, Christos Skourlas: Fuzzy Interval Number (FIN) Techniques for Cross Language Information Retrieval. ICEIS (2) 2006: 249-256
13EEVassilis G. Kaburlasos, Stelios E. Papadakis: Granular self-organizing map (grSOM) for structure identification. Neural Networks 19(5): 623-643 (2006)
12EEStelios 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)
11 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
10EEVassilis 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)
9 Al Cripps, Vassilis G. Kaburlasos, Nghiep Nguyen, Stelios E. Papadakis: Improved Experimental Results Using Fuzzy Lattice Neurocomputing (FLN) Classifiers. MLMTA 2003: 161-166
8 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)
7EEVassilios 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)
6EEVassilios 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)
5EEVassilis G. Kaburlasos, Vassilios Petridis: Fuzzy Lattice Neurocomputing (FLN) models. Neural Networks 13(10): 1145-1170 (2000)
4 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)
3 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
2EEVassilios Petridis, Vassilis G. Kaburlasos: Fuzzy lattice neural network (FLNN): a hybrid model for learning. IEEE Transactions on Neural Networks 9(5): 877-890 (1998)
1EEDwight 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)

Coauthor Index

1Theodoros Alevizos [14] [19]
2Ioannis N. Athanasiadis [15]
3Dave A. Baker [3] [4]
4Petros Belsis [19]
5Peter N. Brett [3] [4]
6Al Cripps [9]
7Dwight D. Egbert [1]
8Pavlina Fragkou [8]
9Philip H. Goodman [1]
10Athanasios Kehagias [8] [16]
11Catherine Marinagi [11] [14] [21]
12Pericles A. Mitkas [15]
13Lefteris Moussiades [22]
14Nghiep Nguyen [9]
15Stelios E. Papadakis [9] [12] [13] [19] [23]
16Vassilios Petridis [2] [3] [4] [5] [6] [7] [8]
17Gerhard X. Ritter [20]
18Christos Skourlas [14] [19]
19Ioannis B. Theocharis (John B. Theocharis, J. B. Theocharis) [12]
20Vassilis Tsoukalas [11] [21]
21Panagiotis Tzionas [12]
22Athena Vakali [22]
23John H. Witchey [1]

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Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)