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A. J. Gonzalez, DeMara, R. F., and Georgiopoulos, M., “Vehicle model generation and optimization for embedded simulation”, Simulation Interoperability Workshop, pp. 206–213, 1998.

G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Using Self-Organizing Maps to Learn Geometric Hash Functions for Model-Based Object Recognition”, IEEE Transactions on Neural Networks, vol. 9.3, pp. 560–570, 1998.

G. Bebis, Georgiopoulos, M., and da Lobo, V. N., “Using self-organizing maps to learn geometric hash functions for model-based object recognition”, IEEE Transactions on Neural Networks, vol. 9, pp. 560-570, 1998.

A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using context-based neural networks to maintain coherence in distributed simulations”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 417-172, 2007.

A. Gonzalez, Georgiopoulos, M., and DeMara, R., “Using Context-Based Neural Networks to Maintain Coherence Among Entities’ States in a Distributed Simulation”, The Journal of Defense Modeling and Simulation, vol. 4, pp. 147-172, 2007.

G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Using Algebraic Functions of Views for Indexing-Based Object Recognition”, International Conference on Computer Vision, pp. 634–639, 1998.

D. Charalampidis, Kasparis, T., Jones, L., and Georgiopoulos, M., “Use of multifractals to detect anomalous propagation (AP) in weather radar”, Proceedings SPIE; Conference on Signals and Data Processing of Small Targets, pp. 13–22, 2008.

S. Verzi, Heileman, G., Georgiopoulos, M., and Anagnostopoulos, G. C., “Universal approximation with Fuzzy ART and Fuzzy ARTMAP”, Neural Networks, pp. 1987–1992, 2003.

C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “A Unifying Framework for Typical Multitask, Multiple Kernel Learning Problems”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 7, pp. 1287-1297, 2014.

R. C. Watkins, Reynolds, K. M., DeMara, R., Georgiopoulos, M., Gonzalez, A., and Eaglin, R., “TRACKING DIRTY PROCEEDS: EXPLORING DATA MINING TECHNOLOGIES AS TOOLS TO INVESTIGATE MONEY LAUNDERING”, Police Practice and Research, vol. 4.2, pp. 163–178, 2003.

D. Charalampidis, Kasparis, T., and Georgiopoulos, M., “Texture classification using ART-based neural networks and Fractals”, SPIE Conference on Signal Processing,Sensor Fusion,and Target Recognition VII, pp. 212–222, 1998.

M. Georgiopoulos, DeMara, R. F., Gonzalez, A. J., Wu, A. S., Mollaghasemi, M., Gelenbe, E., Kysilka, M., Secretan, J., Sharma, C. A., and Alnsour, A. J., “A Sustainable Model for Integrating Current Topics in Machine Learning Research in the Undergraduate Curriculum”, IEEE Transactions on Education, vol. 52, pp. 503-512, 2009.

C. Christodoulou and Georgiopoulos, M., “Smart adaptive array antennas for wireless communcations”, Proceedings of SPIE; Conference on Digital Wireless Communication III, pp. 75–83, 2001.

C. Sentelle, Anagnostopoulos, G. C., and M. Georgiopoulos, R. DeMara, “A Simple Method for Solving the SVM Regularization Path for Semi-Definite Kernels”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 4, pp. 709-722, 2016.

R. Ramirez-Padron, Foregger, D., Manuel, J., Georgiopoulos, M., and Mederos, B., “Similarity Kernels for Nearest Neighbor-based Outlier Detection”, Lecture Notes in Computer Science, vol. 6065/2010, pp. 159-170, 2010.

S. E. Skarman, Georgiopoulos, M., and Gonzalez, A. J., “Short-term electrical load forecasting using a fuzzy ARTMAP neural network”, Conference on Applications and Science of Computational Intelligence, pp. 181-191, 1998.

T. Kasparis, Charalampidis, D., Georgiopoulos, M., and Rolland, J. P., “Segmentation of textured images based on fractals and image filtering”, Pattern Recognition, vol. 34.10, pp. 1963–1973, 2001.

T. Kasparis, Charalampidis, D., Georgiopoulos, M., and Rolland, J. P., “Segmentation of textured images based on fractals and image filtering”, Pattern Recognition, vol. 34.10, pp. 1963–1978, 2001.

A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, K., “A Scalable and Efficient Outlier Detection Strategy for Categorical Data”, International Conference on Tools with Artificial Intelligence (ICTAI), 2007.

G. C. Anagnostopoulos, Georgiopoulos, M., Verzi, S., and Heileman, G., “Reducing generalization error and category proliferation in ellipsoid ARTMAP via tunable misclassification error tolerance: Boosted Ellipsoid ARTMAP”, Neural Networks, pp. 2650–2655, 2002.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Radial basis function neural network algorithm for adaptivebeamforming in cellular communication systems”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 53–56, 1998.

S. J. Verzi, Heileman, G. L., Georgiopoulos, M., and Healy, M. J., “Rademacher penalization applied to Fuzzy ARTMAP and Boosted ARTMAP”, Proceedings of the International Joint Conference on Neural Networks, pp. 1191–1196, 2001.

G. C. Anagnostopoulos and Georgiopoulos, M., “Putting the utility of match tracking in Fuzzy ARTMAP training to the test”, pp. 1–6, 2003.

M. Georgiopoulos, Dagher, I., Heileman, G. L., and Bebis, G., “Properties of Learning of a Fuzzy ART Variant”, Neural Networks, vol. 12.6, pp. 837–850, 1999.

M. Georgiopoulos, Heileman, G. L., and Huang, J., “Properties of learning in ART1”, Neural Networks, vol. 4, pp. 751-758, 1991.

J. Secretan, Georgiopoulos, M., and Castro, J., “A Privacy Preserving Probabilistic Neural Network for Horizontally Partitioned Databases”, 2007.

J. Castro, Secretan, J., Georgiopoulos, M., DeMara, R., Anagnostopoulos, G. C., and Gonzalez, A., “Pipelining of Fuzzy ARTMAP without Matchtracking: Correctness,Performance Bound and Beowulf Evaluation”, Neural Networks, vol. 20.1, pp. 109–128, 2007.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Performance of Radial-Basis Function Networks for Direction of Arrival Estimation with Antenna Arrays”, IEEE Transactions on Antennas and Propagation, vol. 45.11, pp. 1611–1617, 1997.

G. G. M. M. A. J. H. J.J. Vargas, R.F. DeMara, “PDU Bundling and Replication for Reduction of Distributed Simulation Communication Traffic”, Methodology,Technology,Journal of Defense Modeling and Simulation: Applications, vol. 1.3, pp. 171–183, 2004.

J. J. Vargas, DeMara, R. F., Gonzalez, A. J., Georgiopoulos, M., and Marshall, H., “PDU Bundling and Replication for Reduction of Distributed Simulation Communication Traffic”, Journal of Defense Modeling and Simulation, vol. 1.3, pp. 171–183, 2004.

J. Castro, Georgiopoulos, M., DeMara, R., and Gonzalez, A., “A Partitioned Fuzzy ARTMAP implementation for fast processing of large databases on sequential machines”, 2004.

C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Pareto-Path Multi-task Multiple Kernel Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in June 2014), 2014.

C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Pareto-Path Multi-Task Multiple Kernel Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 1, pp. 51-61, 2015.

T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Pareto Optimal Selection via SPRINT-Race”, IEEE Transactions on Cybernetics, vol. 48, no. 2, pp. 596-610, 2018.

J. Secretan, Georgiopoulos, M., Anagnostopoulos, G. C., Tapia, J., Chadha, A., and Huber, B., “Parallelizing the Fuzzy ARTMAP Algorithm on a Beowulf Clusters”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2005), pp. 475–480, 2005.

J. Castro, Georgiopoulos, M., Secretan, J., DeMara, R., Anagnostopoulos, G. C., and Gonzalez, A., “Parallelization of Fuzzy ARTMAP to improve its convergence speed: The network partitioning approach and the data partitioning approach”, Nonlinear Analysis: Theory,Methods and Applications, vol. 63.5-7, pp. e877–e889, 2005.

M. Georgiopoulos, “Packet error probabilities in frequency hopped spread spectrum packet radio networks–Memoryless frequency hopping patterns considered”, IEEE Trans. on Comm., vol. 36, pp. 720-724, 1988.

M. Georgiopoulos, “Packet error probabilities in direct sequence spread spectrum packet radio networks”, IEEE Trans. on Comm., vol. 38, pp. 1599-1606, 1990.

M. Georgiopoulos, Koufakou, A., Anagnostopoulos, G. C., and Kasparis, T., “Over-training in Fuzzy ARTMAP: Myth or Reality?”, Proceedings of the International Joint Conference on Neural Networks, pp. 1186–1190, 2001.

H. G. L. I. Dagher, M. Georgiopoulos, “An Ordering Algorithm for Pattern Presentation in Fuzzy ARTMAP That Tends to Improve Generalization Performance”, IEEE Transactions on Neural Networks, vol. 10.4, pp. 768–778, 1999.

I. Dagher, Georgiopoulos, M., Heileman, G. L., and Bebis, G., “Ordered fuzzy ARTMAP: a fuzzy ARTMAP algorithm with a fixed order of pattern presentation”, IEEE International Joint Conference on Neural Networks, pp. 1717–1722, 1998.

M. Georgiopoulos, Fernlund, H., Bebis, G., and Heileman, G., “Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter”, Neural Networks, vol. 9.9, pp. 1541-1559, 1996.

G. Bebis and Georgiopoulos, M., “Optimal feed-forward neural network architectures”, IEEE Potentials, pp. 27-31, 1994.

A. Vartak, Georgiopoulos, M., and Anagnostopoulos, G. C., “On-line Gaussae Newton-based learning for fully recurrent neural networks”, Nonlinear Analysis, vol. 63, pp. e867–e876, 2005.

S. Verzi, Heileman, G., Georgiopoulos, M., and Anagnostopoulos, G. C., “Off-line structural risk minimization and BARTMAP-S”, Neural Networks, pp. 2533–2538, 2002.

A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A novel approach to adaptive nulling with neural networks”, Southeastcon, pp. 216–219, 1998.

A. Koufakou, Secretan, J., and Georgiopoulos, M., “Non-derivable itemsets for fast outlier detection in large high dimensional categorical data”, Knowledge and Information Systems, pp. 1-29, 2010.

M. Georgiopoulos, Heileman, G. L., and J. Huang, “The N-N-N conjecture in ART1”, Neural Networks, vol. 5, pp. 745-753, 1992.

G. C. Anagnostopoulos and Georgiopoulos, M., “New geometrical perspective of fuzzy ART and fuzzy ARTMAP learning”, Proceedings of SPIE; Conference on Applications and Science of Computational Intelligence IV, pp. 22–32, 2001.

G. C. Anagnostopoulos and Georgiopoulos, M., “New Geometrical Concepts in Fuzzy-ART and Fuzzy-ARTMAP: Category Regions”, IEEE-INNS International Joint Conference on Neural Networks (IJCNN 2001), pp. 32–37, 2001.

E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “A neural-network-based linearly constrained minimum variance beamformer”, Microwave and Optical Technology Letters, vol. 21.6, pp. 451–455, 1999.

A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “A Neural Network-Based Smart Antenna for Multiple Source Tracking”, IEEE Transactions on Antennas and Propagation, vol. 48.5, pp. 768–776, 2000.

A. H. E. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays”, IEEE Transactions on Antennas and Propagation, vol. 46, pp. 1891-1893, 1998.

E. A. H. Zooghby, Christodoulou, C., and Georgiopoulos, M., “Neural Network-Based Adaptive Beamforming for One- and Two-Dimensional Antenna Arrays”, IEEE Transactions on Antennas and Propagation, vol. 46.1, pp. 1891–1893, 1998.

C. G. Christodoulou, Zooghby, E. A. H., and Georgiopoulos, M., “Neural network processing for adaptive array antennas”, IEEE Antennas and Propagation Society International Symposium, pp. 2584–2587, 1999.

E. A. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Neural Network based beamforming for interference cancellation”, Conference on Applications and Science of Computational Intelligence, pp. 420–429, 1998.

G. L. Heileman, Papadourakis, G. M., and Georgiopoulos, M., “A neural network associative memory for real-time applications”, Neural Computation, vol. 2, pp. 107-115, 1990.

C. Li, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1468-1479, 2015.

C. Li, Georgiopoulos, M., and Anagnostopoulos, G. C., “Multi-Task Classification Hypothesis Space with Improved Generalization Bounds ”, IEEE Transactions on Neural Networks and Learning Systems, vol. accepted for publication (acceptance was communicated in July 2014), 2014.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple sources neural network direction finding with arbitrary separations”, IEEE-APS Conference on Antennas and Propagation for Wireless Communications, pp. 57–60, 1998.

C. Christodoulou, Georgiopoulos, M., and Zooghby, E. A., “Multiple Source Angle of Arrival Estimation using Neural-Network-based Smart Antennas”, Proceedings SPIE; Conference on Digital Wireless Communications II, pp. 94–99, 2000.

E. A. H. Zooghby, Christodoulou, C. G., and Georgiopoulos, M., “Multiple mobile user tracking with neural network-based adaptive array antennas”, SPIE Conference on Digital Wireless Communications, pp. 88–97, 1999.

T. Zhang, M. Georgiopoulos, R. DeMara,, and Anagnostopoulos, G. C., “Multi-Objective Model Selection via Racing”, IEEE Transactions on Cybernetics, vol. 46, no. 8, pp. 1863-1876, 2015.

X. Rui, Anagnostopoulos, G. C., and II, W. D., “Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 4., pp. 65–77, 2007.

A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.

A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: An adaptive multi-objective approach to evolving ART architectures”, IEEE Transactions on Neural Networks, vol. 21, pp. 529-550, 2010.

A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “Modeling Semi-Automated Forces with Neural Networks: Performance Improvement through a Modular Approach”, 2000.

A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G. C., “M-GFAM:An Elegant Approach to Genetically Optimize Fuzzy ARTMAP Neural Network Architectures”, Proceedings of the 8th International Conference on Natural Computing (ICNC 2007),part of the 10th Joint Conference on Information Sciences (JCIS 2007), pp. 1617-1623, 2007.

J. Secretan, Georgiopoulos, M., Maidhof, I., Shibly, P., and Hecker, J., “Methods for Parallelizing the Probabilistic Neural Network on a Beowulf Cluster Computer”, 2006.

A. Henninger, Gonzalez, A., Georgiopoulos, M., and DeMara, R., “The Limitations of Static Performance Metrics for Dynamic Tasks Learned Through Observation”, Proceedings of the Tenth Conference on Computer Generated Forces and Behavioral Representation, pp. 147–154, 2001.

H. K. Fernlund, Gonzalez, A. J., Georgiopoulos, M., and DeMara, R., “Learning tactical human behavior through observation of human performance”, Cybernetics–Part B: Cybernetics,Man,IEEE Transactions on Systems, vol. 36.1, pp. 128–140, 2006.

M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, vol. 68, pp. 361-384, 2011.

M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 2010.

G. Bebis, Georgiopoulos, M., da Lobo, V. N., and Shah, M., “Learning affine transformations”, Pattern Recognition, vol. 32.10, pp. 1783–1799, 1999.

M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “k-Norm Misclassification Rate Estimation for Decision Trees”, Proceedings of the 11th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2007), pp. 163–168, 2007.

M. Zhong, Georgiopoulos, M., and Anagnostopoulos, G. C., “A k -norm pruning algorithm for decision tree classifiers based on error rate estimation”, Machine Learning, vol. 71, pp. 55-88, 2008.

J. Reeder, Miguez, R., Sparks, J., Georgiopoulos, M., and Anagnostopoulos, G. C., “Interactively Evolved Modular Neural Networks for Game Agent Control”, IEEE Symposium on Computational Intelligence and Games (CIG 08, pp. 167–174, 2008.

J. Reeder, Gita, S., Georgiopoulos, M., and Anagnostopoulos, G. C., “Intelligent Trading Agents for Massively Multi-player Game Economies”, Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 102–107, 2008.

G. Bebis, Georgiopoulos, M., Shah, M., and da Lobo, V. N., “Indexing Based on Algebraic Functions of Views”, Computer Vision and Image Understanding, vol. 72.3, pp. 360–378, 1998.

C. Young, Georgiopoulos, M., Hagen, S., Geiger, C., Dagley-Falls, M., Islas, A., Ramsey, P., Lancey, P., Forde, D., and Bradbury, E., “Improving Student Learning in Calculus through Applications”, International Journal of Mathematical Education in Science and Technology, vol. 42, pp. 591-604, 2011.

G. C. Anagnostopoulos and Georgiopoulos, M., “Hypersphere ART and ARTMAP for Unsupervised and Supervised,Incremental Learning”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 59–64, 2000.

S. Verzi, Heileman, G., Georgiopoulos, M., and Healy, M., “Hierarchical ARTMAP”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 41–46, 2008.

G. Rabadi, Anagnostopoulos, G. C., and Mollaghasemi, M., “A heuristic algorithm for the just-in-time single machine scheduling problem with setups: A comparison with simulated annealing”, vol. 32, pp. 326–335, 2007.

A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Wu, A. S., Mollaghasemi, M., and Anagnostopoulos, G. C., “GFAM:Evolving Fuzzy ARTMAP Neural Networks”, vol. 20.8, pp. 874–892, 2007.

A. Al-Dairaiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Wu, A. S., and Anagnostopoulos, G., “GFAM Evolving Fuzzy ARTMAP Neural Networks”, Neural Networks journal, vol. 20, pp. 874-892, 2007.

R. Miguez, Georgiopoulos, M., and Kaylani, A., “A Genetically Engineered Probabilistic Neural Network”, Nonlinear Analysis: Theory, Methods & Applications, vol. 73, pp. 1783-1791, 2010.

A. Al-Daraiseh, Kaylani, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Kaburlasos, V. G., “Genetically Engineered ART Architectures”, Heidelberg: Springer-Verlag,in Computational Intelligence Based on Lattice Theory,Studies in Computational Intelligence, vol. 67, pp. 233–262, 2007.

G. Bebis, Uthiram, S., and Georgiopoulos, M., “Genetic Search for Face Detection and Verification”, IEEE International Conference on Information,Intelligence and Systems, pp. 360–367, 1999.

A. Kaylani, Al-Daraiseh, A., Georgiopoulos, M., Mollaghasemi, M., Anagnostopoulos, G. C., and Wu, A. S., “Genetic Optimization of ART Neural Network Architectures”, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2007), pp. 379–384, 2007.

J. Reeder and Georgiopoulos, M., “Generative Neural Networks for Multi-Task Life-Long Learning”, The Computer Journal, vol. 57, no. 3, pp. 427-450, 2014.

M. Zhong, Georgiopoulos, M., Anagnostopoulos, G. C., and Mollaghasemi, M., “Generalized Entropy for Splitting Numerical Attributes in Decision Tree Classifiers”, Proceedings of the 19th International Florida Artificial Intelligence Research Society (FLAIRS) Conference (FLAIRS 2006), pp. 604–609, 2006.

G. L. Heileman, Georgiopoulos, M., and Roome, W. D., “A general framework for concurrent simulation on neural network models”, IEEE Transactions on Software Engineering, vol. 18, pp. 551-562, 1992.

M. Zhong, Coggeshall, D., Georgiopoulos, M., Anagnostopoulos, G. C., Mollaghasemi, M., and Richie, S., “Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks”, Proceedings of the 2006 IEEE-INNS-ENNS International Joint Conference on Neural Networks, pp. 1870–1877, 2006.

N. Shorter and Kasparis, T., “Fuzzy SART Clustering for 3D Reconstruction from Irregular LIDAR Data”, vol. 2.8, pp. 1122 – 1129, 2006.

C. Sentelle, Hong, S. L., Anagnostopoulos, G. C., and Georgiopoulos, M., “A fuzzy gap statistic for Fuzzy C-Means”, Proceedings of the 11th IASTED International Conference on Artificial, 2007.

I. Dagher, Georgiopoulos, M., Heileman, G., and Bebis, G., “Fuzzy ARTVar: An Improved Fuzzy ARTMAP Algorithm”, International Joint Conference on Neural Networks, pp. 1688–1693, 1998.

D. Charalampidis, Kasparis, T., Georgiopoulos, M., and Rolland, J., “A Fuzzy ARTMAP based classification of natural textures”, Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, pp. 507–511, 1999.

J. Huang, Georgiopoulos, M., and Heileman, G. L., “Fuzzy ART properties”, Neural Networks, vol. 8, pp. 203-213, 1995.

D. Charalampidis, Anagnostopoulos, G. C., Georgiopoulos, M., and Kasparis, T., “Fuzzy ART and ARTMAP with adaptive weighted distances”, Proceedings of SPIE,Conference on Applications and Science of Computational Intelligence V, vol. 4739, pp. 86–97, 2002.

G. Bebis, Deaconu, T., and Georgiopoulos, M., “Fingerprint identification using Delaunay triangulation”, IEEE International Conference on Information,Intelligence and Systems, pp. 452–459, 1999.

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