You are here

Home

Publications

Export 67 results:
Author Title [ Type(Desc)] Year
Filters: First Letter Of Last Name is K  [Clear All Filters]
Conference Paper
J. Secretan, Koufakou, A., and Georgiopoulos, M., “APHID: A practical architecture for high-performance, privacy preserving, data-mining”, in DMIN 2009, Las Vegas,NV, 2009.
A. Koufakou, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local satte and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
A. Koufakou, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local satte and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
K. Reynolds, Wakchaure, A., Kursun, O., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Burglary data mining – A three tiered approach: Local state and nation-wide”, in the 2nd Annual GIS Symposium at TU, Troy, Alabama, 2005.
D. Charalampidis, Georgiopoulos, M., and Kasparis, T., “Classification of noisy signals using Fuzzy ARTMAP neural networks”, in the International Joint Conference on Neural Networks, Como, Italy, 2000.
A. Koufakou, Weihs, N., Georgiopoulos, M., and Al-Daraiseh, A., “Comparisons of Gaussian ARTMAP and Distributed Gaussian ARTMAP: The Category Proliferation problem”, in ANNIE 2006, St. Louis, Missouri, 2006.
G. Bebis, Georgiopoulos, M., and Kasparis, T., “Coupling weight elimination and genetic algorithms”, in International Conference on Neural Networks (ICNN), Washington, DC, 1996.
M. Georgiopoulos, Gelenbe, E., DeMara, R., Gonzalez, A., Kysilka, M., Mollaghasemi, M., Wu, A., Russell, I., Anagnostopoulos, G., and Secretan, J., “CRCD Experiences at the University of Central Florida: An NSF Project”, in the ASEE 2005 Annual Conference and Exposition, Portland Oregon, 2005.
K. Reynolds, Kursun, O., Georgiopoulos, M., and Eaglin, R., “Development of an Artificial Intelligence Clustering Algorithm to Detect Auto Theft Recovery Patterns”, in GIS Symposium 2004, Troy, AL, 2004.
K. Reynolds, Kursun, O., Eaglin, R., Chen, B., and Georgiopoulos, M., “Development of an Artificial Intelligent System for detection and visualization of auto theft recovery patterns”, in Computational Intelligence Conference on Homeland Security and Public Safety (CIHSPS, 2005), Orlando, FL, 2005.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “Efficient Evolution of ART Neural Networks”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), 2008.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, in the 25th International Symposium on Computer and Information Sciences, London, UK, 2010.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “MO-GART: Multi-Objective Optimization of ART Architectures”, in 2008 IEEE Congress on Evolutionary Computation (IEEE CEC 2008), Hong Kong, 2008.
T.Rubio, Zhang, T., Georgiopoulos, M., and Kaylani, A., “Multi-Objective Evolutionary Optimization of Exemplar-Based Classifiers: A PNN Test Case”, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA, 2011.
T. Kasparis, Georgiopoulos, M., and Payne, E., “Non-linear filtering techniques for narrow-band interference rejection in direct sequence spread-spectrum systems”, in MILCOM 91, McLean, Virginia, 1991.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in the ASEE 2005 Annual Conference and Exposition, Portland, Oregon, 2005.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in the ASEE 2005 Annual Conference and Exposition, Portland, Oregon, 2005.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in 2006 ASEE, Chicago, Illinois, 2006.
G. C. Anagnostopoulos, Georgiopoulos, M., Ports, K., Richie, S., Cardinale, N., White, M., Kepuska, V., Chan, P. K., Wu, A., and Kysilka, M., “Project EMD-MLR: Educational Materials Development and Research in Machine Learning for Undergraduate students”, in 2006 ASEE, Chicago, Illinois, 2006.
A. Koufakou, Ortiz, E., Georgiopoulos, M., Anagnostopoulos, G. C., and Reynolds, M. K., “A scalable and efficient otlier detection strategy for categorical data”, in Annual IEE International Conference on Tools with Artificial Intelligence, 2007 (ICTAI 2007),, Patras, Greece, 2007.
W. J. Park, Jones, L., Charalampidis, D., Kasparis, T., and Georgiopoulos, M., “Sea-Ice extent classification using active/passive microwave measurements from QuickScat”, in AGU Spring meeting, Washington DC, 2001.
D. Charalampidis, Kasparis, T., Jones, W. L., and Georgiopoulos, M., “Use of multi-fractals to detect anomalous propagation (AP) in weather data”, in Proceedings SPIE; Conference on Signals and Data Processing of Small Targets, Orlando, FL, 2000.
Journal Article
N. Shorter and Kasparis, T., “3D Reconstruction of Irregular Spaced LIDAR”, Proceedings of the 6th WSEAS International Conference on Systems Theory and Scientific Computation, 2006.
A. Kaylani, Georgiopoulos, M., Mollaghasemi, M., and Anagnostopoulos, G., “AG-ART: An Adaptive Method of Evolving ART Architectures”, Neurocomputing, vol. 72, pp. 2079-2092, 2009.
O. Kursun, Koufakou, A., Wakchaure, A., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Answer: approximate Name Search with Errors in Large Databases by a Novel Approach Based on Prefix-dictionary”, International Journal on Artificial Intelligence Tools, vol. 15.5, pp. 839–848, 2006.
O. Kursun, Koufakou, A., Wakchaure, A., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “Answer: approximate Name Search with Errors in Large Databases by a Novel Approach Based on Prefix-dictionary”, International Journal on Artificial Intelligence Tools, vol. 15.5, pp. 839–848, 2006.
J. Secretan, Koufakou, A., Georgiopoulos, M., and Cardona, K., “APHID: An architecture for private, high-performance integrated data-mining”, Journal of Future Generation Computer Systems, vol. 26, pp. 891-904, 2010.
D. Charalampidis, Anagnostopoulos, G. C., Kasparis, T., and Georgiopoulos, M., “Classification of noisy patterns using ARTMAP-based neural networks”, Proceedings SPIE; Conference on Visual Information Processing IX, pp. 2-13, 2008.
D. Charalampidism, Georgiopoulos, M., and Kasparis, T., “Classification of Noisy Signals Using Fuzzy ARTMAP Neural Networks”, Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 53–58, 2000.
D. Chralampidis, Kasparis, T., and Georgiopoulos, M., “Classification of noisy signals using fuzzy ARTMAP neural networks”, Neural Networks, vol. 12.5, pp. 1023–1036, 2001.
A. Koufakou, Weihs, N., Georgiopoulos, M., and Al-Daraiseh, A., “Comparisons of Gaussian ARTMAP and Distributed Gaussian ARTMAP Classifiers - The Category Proliferation Problem”, Evolutionary Programming,Complex Systems and Artificial Life also presented at the 2006 Artificial Neural Networks in Engineering (ANNIE), vol. 16, pp. 695–704, 2006.
G. Bebis, Georgiopoulos, M., and Kasparis, T., “Coupling weight elimination with genetic algorithms to reduce network size and preserve generalization”, Neurocomputing, pp. 167–194, 1997.
M. Georgiopoulos, Russell, I., Castro, J., Wu, A., Kysilka, M., and DeMara, R., “A CRCD Experience: Integrating machine learning modules into introductory engineering and science programming courses”, Proceedings of the 2003 American Society for Engineering Education Annual Conference & Exposition, 2003.
M. Georgiopoulos, Castro, J., Gelenbe, E., DeMara, R., Gonzalez, A., and Kysilka, M., “CRCD Experiences at the University of Central Florida: An NSF Project”, Proceedings of the ASEE 2004 Annual Conference and Exposition, 2004.
A. Koufakou, Georgiopoulos, M., Anagnostopoulos, G. C., and Kasparis, T., “Cross-validation in Fuzzy ARTMAP for large databases”, Neural Networks, vol. 14.9, pp. 1279-1291, 2001.
A. Koufakou, Georgiopoulos, M., Anagnostopoulos, G. C., and Kasparis, T., “Cross-validation in Fuzzy ARTMAP for large databases”, Neural Networks, vol. 14.9, pp. 1279-1291, 2001.
M. Georgiopoulos, Koufakou, A., Anagnostopoulos, G. C., and Kasparis, T., “Cross-Validation in Fuzzy ARTMAP Neural Networks for Large Sample Classification Problems”, Proceedings of SPIE; Applications and Science of Computational Intelligence IV, 2001.
M. Georgiopoulos, Koufakou, A., Anagnostopoulos, G. C., and Kasparis, T., “Cross-Validation in Fuzzy ARTMAP Neural Networks for Large Sample Classification Problems”, Proceedings of SPIE; Applications and Science of Computational Intelligence IV, 2001.
A. Koufakou, Georgiopoulos, M., and Anagnostopoulos, G. C., “Detecting Outliers in High-Dimensional Datasets with Mixed Attributes”, International Conference on Data Mining (DMIN 2008), 2008.
J. Klodzinski, Al-Daraiseh, A., Georgiopoulos, M., and Al-Deek, H. M., “Development of a java applet for generating truck trips from freight data”, Transportation Research Record No. 1870, pp. 10–17, 2004.
O. Kursun, Koufakou, A., Chen, B., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “A Dictionary-Based Approach to Fast and Accurate Name Matching in Large Law Enforcement Databases”, IEEE Intelligence and Security Informatics (ISI) Conference, pp. 72–82, 2006.
O. Kursun, Koufakou, A., Chen, B., Georgiopoulos, M., Reynolds, K., and Eaglin, R., “A Dictionary-Based Approach to Fast and Accurate Name Matching in Large Law Enforcement Databases”, IEEE Intelligence and Security Informatics (ISI) Conference, pp. 72–82, 2006.
A. Koufakou and Georgiopoulos, M., “A fast outlier detection strategy for distributed high dimensional datasets with mixed attributes”, Data Mining and Knowledge Discovery, vol. 20, pp. 259-289, 2010.
A. Koufakou, Secretan, J., Reeder, J., Cardona, K., and Georgiopoulos, M., “Fast Parallel Outlier Detection for Categorical Datasets using MapReduce”, IEEE World Congress on Computational Intelligence (WCCI), 2008.
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.
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.
N. Shorter and Kasparis, T., “Fuzzy SART Clustering for 3D Reconstruction from Irregular LIDAR Data”, vol. 2.8, pp. 1122 – 1129, 2006.
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.
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.
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.
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-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.
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.
M. Georgiopoulos, Li, C., and Kocak, T., “Learning in the Feed-Forward Random Neural Network: A Critical Review”, Performance Evaluation, 2010.
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.
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.
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. 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, 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.
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.
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.
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.
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.
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.
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.
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.