Information Characterization & Exploitation

Information Characterization & Exploitation

Intelligent Systems: From Theory to Practice

Publication

  2018 (6)
Infrasound Threat Classification: A Statistical Comparison of Deep Learning Architectures. Solomon, M.; Smith, K.; Bryan, K.; Smith, A. O; and Peter, A. M In SPIE: Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing, 2018.
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Near-field Infrasound Classification of Rocket Launch Signatures. Smith, K.; Bryan, K.; Solomon, M.; Smith, A. O; and Peter, A. M In SPIE: Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing, 2018.
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Deep Wavelet Scattering Features for Infrasonic Threat Identification. Bryan, K.; Solomon, M.; Smith, K.; Smith, A. O; and Peter, A. M In SPIE: Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing, 2018.
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A Comparison of Grid and Cloud Computing Technology. Salih, A.; and Smith, A. O International Journal of Engineering Research and Development, 14(1): 1-10. 2018.
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Pareto-Optimal Model Selection via SPRINT-Race. Zhang, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. IEEE Transactions on Cybernetics, 48(2): 596--610. 2018.
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Learning a Novel Detection Metric for the Detection of O'Connell Effect Eclipsing Binaries. Johnston, K.; Haber, R.; Knote, M.; Caballero-Nieves, S. M.; Peter, A.; and Petit, V. In American Astronomical Society Meeting Abstracts, volume 231, 2018.
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  2017 (5)
Functional Data Classification by Discriminative Interpolation with Features. Haber, R.; Rangarajan, A.; Mijatovic, N.; Smith, A. O; Peter, A. M.; Smth, A. O; and Peter, A. M. In International Work Conference on Time Series Analysis, pages 1120--1131, 2017.
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Signal Classification Using Covariance Matrices: A Riemannian Geometry Framework. Divins, S. G.; Beard, J. S.; Mijatovic, N.; Smith, A. O; Peter, A. M.; Clauter, D. A.; and Haber, R. In International Work Conference on Time Series Analysis, pages 400--410, 2017.
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Time Series Data Classification using Discriminative Interpolation with Sparsity. Mijatovic, N.; Haber, R.; Rangarajan, A.; Smith, A. O; and Peter, A. M In International Conference on Computational Science and Computational Intelligence, 2017.
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Variable Star Signature Classification using Slotted Symbolic Markov Modeling. Johnston, K. B; and Peter, A. M New Astronomy, 50: 1--11. 2017.
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The Geometry of Orthogonal-Series, Square-Root Density Estimators: Applications in Computer Vision and Model Selection. Peter, A. M.; Rangarajan, A.; and Moyou, M. In Computational Information Geometry, pages 175--215. Springer, Cham, 2017.
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  2016 (9)
Video Tracking with Probabilistic Cooccurrence Feature Extraction. Smith, K.; and Smith, A. O In International Symposium on Visual Computing, Lecture Notes in Computer Science, volume 10073 LNCS, pages 504--513, 2016.
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A Category Space Approach to Supervised Dimensionality Reduction. Smith, A. O; and Rangarajan, A. . oct 2016.
A Category Space Approach to Supervised Dimensionality Reduction [link]Paper   bibtex   abstract
Adaptive Foreground Extraction for Deep Fish Classification. Seese, N.; Myers, A.; Smith, K.; and Smith, A. O In 2016 ICPR 2nd Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI), pages 19--24, dec 2016. IEEE
Adaptive Foreground Extraction for Deep Fish Classification [link]Paper   doi   bibtex
A Simple Method for Solving the SVM Regularization Path for Semidefinite Kernels. Sentelle, C.; Anagnostopoulos, G. C.; and Georgiopoulos, M. IEEE Transactions on Neural Networks and Learning Systems, 27(4): 709-722. April 2016.
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Multi-Objective Model Selection via Racing. Zhang, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. Cybernetics, IEEE Transactions on, 46(8): 1863-1876. 2016.
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A Grassmannian Graph Approach to Affine Invariant Feature Matching. Moyou, M.; Corring, J.; Peter, A.; and Rangarajan, A. arXiv preprint arXiv:1601.07648, . 2016.
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CASAIR: Content and Shape-Aware Image Retargeting and Its Applications. Qi, S.; Chi, Y. J.; Peter, A. M.; and Ho, J. IEEE Transactions on Image Processing, 25(5): 2222--2232. 2016.
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LBO-Shape densities: A unified framework for 2D and 3D shape classification on the hypersphere of wavelet densities. Moyou, M.; Ihou, K. E.; and Peter, A. M. Computer Vision and Image Understanding, 152: 142--154. 2016.
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Remote Sensing with Mobile LiDAR and Imaging Sensors for Railroad Bridge Inspections. Otero, L. D.; Peter, A. M.; and Moyou, M. Technical Report 2016.
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  2015 (11)
Bayesian Fusion of Back Projected Probabilities (BFBP): Co-occurrence Descriptors for Tracking in Complex Environments. B, M. M.; Ihou, K. E.; Haber, R.; Smith, A. O; Peter, A. M; Fox, K.; and Henning, R. Advanced Concepts in Intelligent Systems, 9386: 167--180. 2015.
Bayesian Fusion of Back Projected Probabilities (BFBP): Co-occurrence Descriptors for Tracking in Complex Environments [link]Paper   doi   bibtex   abstract
Bayesian fusion of back projected probabilities (BFBP): Co-occurrence descriptors for tracking in complex environments. Moyou, M.; Ihou, K.; Haber, R.; Smith, A. O; Peter, A.; Fox, K.; and Henning, R. Volume 9386 2015.
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Hash Function Learning via Codewords. Huang, Y.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Appice, A.; Rodrigues, P. P.; Santos Costa, V.; Soares, C.; Gama, J.; and Jorge, A., editor(s), Machine Learning and Knowledge Discovery in Databases, volume 9284, of Lecture Notes in Computer Science, pages 659-674. Springer International Publishing, 2015.
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Multitask Classification Hypothesis Space With Improved Generalization Bounds. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. Neural Networks and Learning Systems, IEEE Transactions on, 26(7): 1468-1479. July 2015.
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Pareto-Path Multitask Multiple Kernel Learning. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. Neural Networks and Learning Systems, IEEE Transactions on, 26(1): 51-61. Jan 2015.
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Multi-Task Learning with Group-Specific Feature Space Sharing. Yousefi, N.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Appice, A.; Rodrigues, P. P.; Santos Costa, V.; Gama, J.; Jorge, A.; and Soares, C., editor(s), Machine Learning and Knowledge Discovery in Databases, volume 9285, of Lecture Notes in Computer Science, pages 120-136. Springer International Publishing, 2015.
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SPRINT Multi-Objective Model Racing. Zhang, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, of GECCO '15, pages 1383--1390, New York, NY, USA, 2015. ACM
SPRINT Multi-Objective Model Racing [link]Paper   doi   bibtex
A wireless sensor networks' analytics system for predicting performance in on-demand deployments. Otero, C. E.; Haber, R.; Peter, A. M.; AlSayyari, A.; and Kostanic, I. IEEE Systems Journal, 9(4): 1344--1353. 2015.
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Research directions for engineering big data analytics software. Otero, C. E.; and Peter, A. M. IEEE Intelligent Systems, 30(1): 13--19. 2015.
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Discriminative interpolation for classification of functional data. Haber, R.; Rangarajan, A.; and Peter, A. M. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages 20--36, 2015. Springer, Cham
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Bayesian fusion of back projected probabilities (BFBP): co-occurrence descriptors for tracking in complex environments. Moyou, M.; Ihou, K. E.; Haber, R.; Smith, A. O.; Peter, A. M; Fox, K.; and Henning, R. In International Conference on Advanced Concepts for Intelligent Vision Systems, pages 167--180, 2015. Springer, Cham
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  2014 (15)
Conic Multi-task Classification. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Calders, T.; Esposito, F.; Hüllermeier, E.; and Meo, R., editor(s), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II, volume 8725, of Lecture Notes in Computer Science, pages 193--208, 2014. Springer
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Online model racing based on extreme performance. Zhang, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Arnold, D. V., editor(s), Genetic and Evolutionary Computation Conference, GECCO '14, Vancouver, BC, Canada, July 12-16, 2014, pages 1351--1358, 2014. Association for Computing Machinery (ACM) [\textbfnominee; Best Paper Award]
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Path optimization for oil probe. Smith, A. O; Rahmes, M.; Blue, M.; and Peter, A. In Proceedings of SPIE - The International Society for Optical Engineering, volume 9106, 2014. International Society for Optics and Photonics
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Graph segmentation and support vector machines for bare earth classification from lidar. Shorter, N.; Smith, O.; Smith, P.; and Rahmes, M. In Proceedings of SPIE - The International Society for Optical Engineering, volume 9080, 2014.
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Derivative free optimization using a population-based stochastic gradient estimator. Khayrattee, A.; and Anagnostopoulos, G. C. In Arnold, D. V., editor(s), Genetic and Evolutionary Computation Conference, (GECCO '14), Vancouver, BC, Canada, July 12-16, 2014, pages 983--990, 2014. Association for Computing Machinery (ACM) [\textbfnominee; Best Paper Award]
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A Unifying Framework for Typical Multitask Multiple Kernel Learning Problems. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. Neural Networks and Learning Systems, IEEE Transactions on, 25(7): 1287-1297. July 2014.
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Genetic and Evolutionary Computation Conference, GECCO '14, Vancouver, BC, Canada, July 12-16, 2014. Arnold, D. V. , editor . 2014.ACM.
Genetic and Evolutionary Computation Conference, GECCO '14, Vancouver, BC, Canada, July 12-16, 2014 [link]Paper   bibtex   buy
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II. Calders, T.; Esposito, F.; Hüllermeier, E.; and Meo, R. , editor s. Volume 8725, of Lecture Notes in Computer Science. 2014.Springer.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part II [link]Paper   doi   bibtex   buy
Parallel Hierarchical Affinity Propagation with MapReduce. Rose, D. M.; Rouly, J. M.; Haber, R.; Mijatovic, N.; and Peter, A. M. In Cloud Engineering (IC2E), 2014 IEEE International Conference on, pages 367--372, 2014. IEEE
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Path optimization for oil probe. Rahmes, M.; Blue, M.; Peter, A. M.; and others In Advanced Environmental, Chemical, and Biological Sensing Technologies XI, volume 9106, pages 91060N, 2014. International Society for Optics and Photonics
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A new energy minimization framework and sparse linear system for path planning and shape from shading. Peter, A. M.; Gurumoorthy, K. S.; Moyou, M.; and Rangarajan, A. In Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing, pages 15, 2014. ACM
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Determining human-perceived level of safety in transportation systems using big data analytics. Otero, C. E; Rossi, M.; Peter, A.; and Haber, R. In Proceedings on the International Conference on Internet Computing (ICOMP), pages 1, 2014. The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)
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LBO-shape densities: Efficient 3D shape retrieval using wavelet density estimation. Moyou, M.; Ihou, K. E.; and Peter, A. M. In Pattern Recognition (ICPR), 2014 22nd International Conference on, pages 52--57, 2014. IEEE
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A systems engineering approach to quantitative comparison of molecular instruments for use on the International Space Station. Lineberger, K.; Levitt, J.; Smith, D. J.; Van Nguyen, T.; and Peter, A. M. Procedia Computer Science, 28: 340--346. 2014.
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A fast eikonal equation solver using the Schrodinger wave equation. Gurumoorthy, K. S.; Peter, A. M.; Guan, B. H.; and Rangarajan, A. arXiv preprint arXiv:1403.1937, . 2014.
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  2013 (7)
3D graph segmentation for target detection in FOPEN LiDAR data. Shorter, N.; Locke, J.; Smith, O.; Keating, E.; and Smith, P. In Proceedings of SPIE - The International Society for Optical Engineering, volume 8731, 2013.
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Point Spread Function (PSF) noise filter strategy for Geiger mode LiDAR. Smith, A. O; Stark, R.; Smith, P.; St Romain, R.; and Blask, S. In Proceedings of SPIE - The International Society for Optical Engineering, volume 8731, 2013. International Society for Optics and Photonics
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Reduced-Rank Local Distance Metric Learning. Huang, Y.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Blockeel, H.; Kersting, K.; Nijssen, S.; and Zelezný, F., editor(s), European Conference on Machine Learning (ECML), volume 8190, of Lecture Notes in Computer Science, pages 224-239, 2013. Springer
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Kernel-based Distance Metric Learning in the Output Space. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN), pages 1--8, 2013. Institute of Electrical and Electronics Engineers (IEEE) [\textbfnominee; Best Paper Award]
Kernel-based Distance Metric Learning in the Output Space [link]Link   doi   bibtex   abstract
S-Race: A Multi-Objective Racing Algorithm. Zhang, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Blum, C.; and Alba, E., editor(s), Genetic & Evolutionary Computation Conference (GECCO), pages 1565-1572, 2013. Association for Computing Machinery (ACM) [\textbffinalist; Best Paper Award]
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Multiwavelet density estimation. Locke, J.; and Peter, A. M. Applied Mathematics and Computation, 219(11): 6002--6015. 2013.
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A support vector machine for terrain classification in on-demand deployments of wireless sensor networks. Haber, R.; Peter, A. M.; Otero, C. E.; Kostanic, I.; and Ejnioui, A. In Systems Conference (SysCon), 2013 IEEE International, pages 841--846, 2013. IEEE
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  2012 (3)
Shape analysis on the hypersphere of wavelet densities. Moyou, M.; and Peter, A. M. In Pattern Recognition (ICPR), 2012 21st International Conference on, pages 2091--2094, 2012. IEEE
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Intelligent system for predicting wireless sensor network performance in on-demand deployments. Otero, C. E.; Kostanic, I.; Peter, A. M.; Ejnioui, A.; and Otero, L D. In Open Systems (ICOS), 2012 IEEE Conference on, pages 1--6, 2012. IEEE
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Software requirement prioritization using fuzzy multi-attribute decision making. Ejnioui, A.; Otero, C. E.; and Qureshi, A. A In Open Systems (ICOS), 2012 IEEE Conference on, pages 1--6, 2012. IEEE
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  2011 (7)
Accelerated learning of Generalized Sammon Mappings. Huang, Y.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 2952-2960, July 2011. Institute of Electrical and Electronics Engineers (IEEE)
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Multinomial Squared Direction Cosines Regression. Iqbal, N. H.; and Anagnostopoulos, G. C. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 3028-3035, July 2011. Institute of Electrical and Electronics Engineers (IEEE)
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Kernel principal subspace Mahalanobis distances for outlier detection. Li, C.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 2528-2535, July 2011. Institute of Electrical and Electronics Engineers (IEEE)
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Efficient Revised Simplex Method for SVM Training. Sentelle, C.; Anagnostopoulos, G. C.; and Georgiopoulos, M. Neural Networks, IEEE Transactions on, 22(10): 1650-1661. Oct. 2011.
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Panchromatic modulation of multispectral imagery. Riley, R. A.; Bakir, T.; Peter, A. M.; and Akbari, M. May~3 2011. US Patent 7,936,949
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Geospatial modeling system and related method using multiple sources of geographic information. Van Workum, J. A; Bell, D. M; Spellman, E.; and Peter, A. M. July~19 2011. US Patent 7,983,474
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An Information Geometry Approach to Shape Density Minimum Description Length Model Selection. Peter, A. M.; and Rangarajan, A. In IEEE Workshop on Information Theory in Computer Vision and Pattern Recognition in conjunction with ICCV 2011, 2011.
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  2010 (7)
An Adaptive Multiobjective Approach to Evolving ART Architectures. Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; Anagnostopoulos, G. C.; Sentelle, C.; and Zhong, M. Neural Networks, IEEE Transactions on, 21(4): 529-550. April 2010.
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Multi-objective memetic evolution of ART-based classifiers. Li, R.; Mersch, T. R.; Wen, O. X.; Kaylani, A.; and Anagnostopoulos, G. C. In Evolutionary Computation (CEC), 2010 IEEE Congress on, pages 1-8, July 2010. Institute of Electrical and Electronics Engineers (IEEE) [\textbfnominee; Best Paper Award]
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Metric representations of data via the Kernel-based Sammon Mapping. Ma, M.; Gonet, R.; Yu, R.; and Anagnostopoulos, G. C. In Neural Networks (IJCNN), The 2010 International Joint Conference on, pages 1-7, July 2010. Institute of Electrical and Electronics Engineers (IEEE)
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Geospatial modeling system providing non-linear inpainting for voids in geospatial model cultural feature data and related methods. Rahmes, M.; Smith, A. O.; Allen, J. D.; Peter, A. M; Yates, H.; and Connetti, S. July~6 2010. US Patent 7,750,902
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Spatial and spectral calibration of a panchromatic, multispectral image pair. Riley, R. A.; Bakir, T.; Peter, A. M.; and Akbari, M. November~2 2010. US Patent 7,826,685
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Structured smoothing for superresolution of multispectral imagery based on registered panchromatic image. Riley, R. A.; Bakir, T.; Peter, A. M.; and Akbari, M. November~16 2010. US Patent 7,835,594
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Decision Framework for Capability Evaluations of Software Engineers using Imprecise Parameters. Otero, L D.; Otero, C. E.; and Peter, A. M. In International Conference on Genetic and Evolutionary Methods, 2010.
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  2009 (6)
An Open Source Framework for Real-Time, Incremental, Static and Dynamic Hand Gesture Learning and Recognition. Alexander, T. C.; Ahmed, H. S.; and Anagnostopoulos, G. C. In Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques, pages 123--130, Berlin, Heidelberg, 2009. Springer-Verlag
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SVM-based target recognition from synthetic aperture radar images using target region outline descriptors. Anagnostopoulos, G. C. Nonlinear Analysis: Theory, Methods & Applications, 71(12): e2934 - e2939. December 2009.
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AG-ART: An adaptive approach to evolving ART architectures. Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; and Anagnostopoulos, G. C. Neurocomputing, 72(10–12): 2079 - 2092. June 2009. Lattice Computing and Natural Computing (JCIS 2007) / Neural Networks in Intelligent Systems Designn (ISDA 2007)
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An efficient active set method for SVM training without singular inner problems. Sentelle, C.; Anagnostopoulos, G. C.; and Georgiopoulos, M. In Neural Networks, 2009. IJCNN 2009. International Joint Conference on, pages 2875-2882, June 2009.
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An algebraic approach to affine registration of point sets. Ho, J.; Peter, A. M.; Rangarajan, A.; and Yang, M. In Computer Vision, 2009 IEEE 12th International Conference on, pages 1335--1340, 2009. IEEE
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Information geometry for landmark shape analysis: Unifying shape representation and deformation. Peter, A. M.; and Rangarajan, A. IEEE transactions on pattern analysis and machine intelligence, 31(2): 337--350. 2009.
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  2008 (11)
Efficient evolution of ART neural networks. Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; and Anagnostopoulos, G. C. In Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on, pages 3456-3463, June 2008.
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Structural and syntactic pattern recognition (SSPR 2008) and statistical techniques in pattern recognition (SPR 2008). Lobo, N. d. V.; Kasparis, T.; Georgiopoulos, M.; Roli, F.; Kwok, J.; Anagnostopoulos, G. C.; and Loog, M. In Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, pages 1-1, Dec 2008.
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Shape-based recognition of targets in synthetic aperture radar images using elliptical Fourier descriptors. Nicoli, L. P.; and Anagnostopoulos, G. C. In Proc. SPIE. 6967, Automatic Target Recognition XVIII, volume 6967, pages 69670G-69670G-12, 2008.
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Interactively evolved modular neural networks for game agent control. Reeder, J.; Miguez, R.; Sparks, J.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In 2008 IEEE Symposium On Computational Intelligence and Games, pages 167-174, Dec 2008.
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A fast revised simplex method for SVM training. Sentelle, C.; Anagnostopoulos, G. C.; and Georgiopoulos, M. In Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, pages 1-4, Dec 2008.
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Clustering irregular spaced lidar TINs for 3D reconstruction. Shorter, N.; Kasparis, T.; Georgiopoulos, M.; and Anagnostopoulos, G. C. 2008.
Clustering irregular spaced lidar TINs for 3D reconstruction [link]Paper   bibtex   abstract
A k-norm pruning algorithm for decision tree classifiers based on error rate estimation. Zhong, M.; Georgiopoulos, M.; and Anagnostopoulos, G. C. Machine Learning, 71(1): 55-88. April 2008. 10.1007/s10994-007-5044-4
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Properties of the k-norm pruning algorithm for decision tree classifiers. Zhong, M.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Pattern Recognition, 2008. ICPR 2008. 19th International Conference on, pages 1-4, Dec 2008.
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Maximum likelihood wavelet density estimation with applications to image and shape matching. Peter, A. M.; and Rangarajan, A. IEEE Transactions on Image Processing, 17(4): 458--468. 2008.
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Shape L’Ane rouge: Sliding wavelets for indexing and retrieval. Peter, A. M.; Rangarajan, A.; and Ho, J. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pages 1--8, 2008. IEEE
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Information geometry for shape analysis: Probabilistic models for shape matching and indexing. Peter, A. M. Ph.D. Thesis, University of Florida, 2008.
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  2007 (15)
Genetically Engineered ART Architectures. Al-Daraiseh, A.; Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; Wu, A.; and Anagnostopoulos, G. C. In Kaburlasos, V.; and Ritter, G., editor(s), Computational Intelligence Based on Lattice Theory, volume 67, of Studies in Computational Intelligence, pages 233-262. Springer Berlin Heidelberg, 2007.
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GFAM: Evolving Fuzzy ARTMAP neural networks. Al-Daraiseh, A.; Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; Wu, A. S.; and Anagnostopoulos, G. C. Neural Networks, 20(8): 874 - 892. 2007.
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Pipelining of Fuzzy ARTMAP Without Matchtracking: Correctness, Performance Bound, and Beowulf Evaluation. Castro, J.; Secretan, J.; Georgiopoulos, M.; DeMara, R. F.; Anagnostopoulos, G. C.; and Gonzalez, A. Neural Networks, 20(1): 109--128. January 2007.
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Genetic Optimization of ART Neural Network Architectures. Kaylani, A.; Al-Daraiseh, A.; Georgiopoulos, M.; Mollaghasemi, M.; Anagnostopoulos, G. C.; and Wu, A. In Neural Networks, 2007. IJCNN 2007. International Joint Conference on, pages 379-384, Aug 2007.
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Genetic Optimization of Art Neural Network Architectures. Kaylani, A.; Georgiopoulos, M.; Mollaghasemi, M.; and Anagnostopoulos, G. C. In Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing, of ASC '07, pages 225--230, Anaheim, CA, USA, 2007. ACTA Press
Genetic Optimization of Art Neural Network Architectures [link]Paper   bibtex
A Scalable and Efficient Outlier Detection Strategy for Categorical Data. Koufakou, A.; Ortiz, E.; Georgiopoulos, M.; Anagnostopoulos, G. C.; and Reynolds, K. In Tools with Artificial Intelligence, 2007. ICTAI 2007. 19th IEEE International Conference on, volume 2, pages 210-217, Oct 2007.
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A heuristic algorithm for the just-in-time single machine scheduling problem with setups: a comparison with simulated annealing. Rabadi, G.; Anagnostopoulos, G. C.; and Mollaghasemi, M. The International Journal of Advanced Manufacturing Technology, 32(3-4): 326-335. 2007.
A heuristic algorithm for the just-in-time single machine scheduling problem with setups: a comparison with simulated annealing [link]Paper   doi   bibtex
On Extending the SMO Algorithm Sub-Problem. Sentelle, C.; Georgiopoulos, M.; Anagnostopoulos, G. C.; and Young, C. In Neural Networks, 2007. IJCNN 2007. International Joint Conference on, pages 886-891, Aug 2007.
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A Fuzzy Gap Statistic for Fuzzy C-means. Sentelle, C.; Hong, S. L.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing, of ASC '07, pages 68--73, Anaheim, CA, USA, 2007. ACTA Press
A Fuzzy Gap Statistic for Fuzzy C-means [link]Paper   bibtex
Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data. Xu, R.; Anagnostopoulos, G. C.; and Wunsch, D. Computational Biology and Bioinformatics, IEEE/ACM Transactions on, 4(1): 65-77. Jan 2007.
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Computational Intelligence in Bioinformatics. Xu, R.; Anagnostopoulos, G. C.; and Wunsch, D. C. Hybrid of Neural Classifier and Swarm Intelligence in Multiclass Cancer Diagnosis with Gene Expression Signatures, pages 1--20. John Wiley & Sons, Inc., 2007. Editors: Gary B. Fogel, David W. Corne, Yi Pan
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Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks. Zhong, M.; Coggeshall, D.; Ghaneie, E.; Pope, T.; Rivera, M.; Georgiopoulos, M.; Anagnostopoulos, G. C.; Mollaghasemi, M.; and Richie, S. Neural Computation, 19(10): 2840--2864. October 2007.
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Experiments with an Innovative Tree Pruning Algorithm. Zhong, M.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Proceedings of the 25th Conference on Proceedings of the 25th IASTED International Multi-Conference: Artificial Intelligence and Applications, of AIAP'07, pages 353--358, Anaheim, CA, USA, 2007. ACTA Press
Experiments with an Innovative Tree Pruning Algorithm [link]Paper   bibtex
K-norm Misclassification Rate Estimation for Decision Trees. Zhong, M.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing, of ASC '07, pages 163--168, Anaheim, CA, USA, 2007. ACTA Press
K-norm Misclassification Rate Estimation for Decision Trees [link]Paper   bibtex
Experiments with Safe mu-ARTMAP: Effect of the Network Parameters on the Network Performance. Zhong, M.; Rosander, B.; Georgiopoulos, M.; Anagnostopoulos, G. C.; Mollaghasemi, M.; and Richie, S. Neural Networks, 20(2): 245--259. March 2007.
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  2006 (7)
GFAM: A Genetic Algorithm Optimization of Fuzzy ARTMAP. Al-Daraiseh, A.; Georgiopoulos, M.; Anagnostopoulos, G. C.; Wu, A.; and Mollaghasemi, M. In Fuzzy Systems, 2006 IEEE International Conference on, pages 315-322, 2006.
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Evaluation of Two Modeling Methods for Generating Heavy-Truck Trips at an Intermodal Facility by Using Vessel Freight Data. Sarvareddy, P.; Al-Deek, H.; Klodzinski, J.; and Anagnostopoulos, G. C. Transportation Research Record: Journal of the Transportation Research Board, 1906: 113-120. 2006.
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Gap-Based Estimation: Choosing the Smoothing Parameters for Probabilistic and General Regression Neural Networks. Zhong, M.; Coggeshall, D.; Ghaneie, E.; Pope, T.; Rivera, M.; Georgiopoulos, M.; Anagnostopoulos, G. C.; Mollaghasemi, M.; and Richie, S. In Neural Networks, 2006. IJCNN '06. International Joint Conference on, pages 1870-1877, 2006.
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Experiments with Safe ARTMAP and Comparisons to Other ART Networks. Zhong, M.; Rosander, B.; Georgiopoulos, M.; Anagnostopoulos, G. C.; Mollaghasemi, M.; and Richie, S. In Neural Networks, 2006. IJCNN '06. International Joint Conference on, pages 720-727, 2006.
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Non-negative maximum likelihood ICA for blind source separation of images and signals with application to hyperspectral image subpixel demixing. Bakir, T.; Peter, A.; Riley, R.; and Hackett, J. In Image Processing, 2006 IEEE International Conference on, pages 3237--3240, 2006. IEEE
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Shape analysis using the Fisher-Rao Riemannian metric: Unifying shape representation and deformation. Peter, A. M.; and Rangarajan, A. In Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on, pages 1164--1167, 2006. IEEE
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A new closed-form information metric for shape analysis. Peter, A.; and Rangarajan, A. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 249--256, 2006. Springer, Berlin, Heidelberg
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  2005 (4)
Parallelization of Fuzzy ARTMAP to improve its convergence speed: The network partitioning approach and the data partitioning approach. Castro, J.; Georgiopoulos, M.; Secretan, J.; DeMara, R. F.; Anagnostopoulos, G. C.; and Gonzalez, A. Nonlinear Analysis: Theory, Methods & Applications, 63(5-7): e877 - e889. 2005. Invited Talks from the Fourth World Congress of Nonlinear Analysts (WCNA 2004)
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An experimental comparison of semi-supervised ARTMAP architectures, GCS and GNG classifiers. Le, Q.; Anagnostopoulos, G. C.; Georgiopoulos, M.; and Ports, K. In Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on, volume 5, pages 3121-3126 vol. 5, July 2005.
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On the design of an ellipsoid ARTMAP classifier within the fuzzy adaptive system ART framework. Peralta, R.; Anagnostopoulos, G. C.; Gomez-Sanchez, E.; and Richie, S. In Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on, volume 1, pages 469-474 vol. 1, July 2005.
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Parallelizing the fuzzy ARTMAP algorithm on a Beowulf cluster. Secretan, J.; Castro, J.; Georgiopoulos, M.; Tapia, J.; Chadha, A.; Huber, B.; Anagnostopoulos, G. C.; and Richie, S. In Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on, volume 1, pages 475-480 vol. 1, July 2005.
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  2004 (2)
A Branch-and-bound Algorithm for the Early/Tardy Machine Scheduling Problem with a Common Due-date and Sequence-dependent Setup Time. Rabadi, G.; Mollaghasemi, M.; and Anagnostopoulos, G. C. Computers & Operations Research, 31(10): 1727--1751. September 2004.
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Multi-class cancer classification by semi-supervised ellipsoid ARTMAP with gene expression data. Xu, R.; Anagnostopoulos, G. C.; and Wunsch, D. In Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE, volume 1, pages 188-191, Sept 2004.
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  2003 (2)
Exemplar-based pattern recognition via semi-supervised learning. Anagnostopoulos, G. C.; Bharadwaj, M.; Georgiopoulos, M.; Verzi, S.; and Heileman, G. In Neural Networks, 2003. Proceedings of the International Joint Conference on, volume 4, pages 2782-2787 vol.4, July 2003.
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Universal approximation with Fuzzy ART and Fuzzy ARTMAP. Verzi, S.; Heileman, G.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Neural Networks, 2003. Proceedings of the International Joint Conference on, volume 3, pages 1987-1992 vol.3, July 2003.
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  2002 (8)
Reducing generalization error and category proliferation in ellipsoid ARTMAP via tunable misclassification error tolerance: boosted ellipsoid ARTMAP. Anagnostopoulos, G. C.; Georgiopoulos, M.; Verzi, S.; and Heileman, G. In Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on, volume 3, pages 2650-2655, 2002.
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A simulated annealing algorithm for the unrelated parallel machine scheduling problem. Anagnostopoulos, G. C.; and Rabadi, G. In Automation Congress, 2002 Proceedings of the 5th Biannual World, volume 14, pages 115-120, 2002.
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Category Regions As New Geometrical Concepts in Fuzzy-ART and Fuzzy-ARTMAP. Anagnostopoulos, G. C.; and Georgiopoulos, M. Neural Networks, 15(10): 1205--1221. December 2002.
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Elipsoid ART/ARTMAP category regions for the choice-by-difference category choice function. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Proc. SPIE 4739, Applications and Science of Computational Intelligence V, volume 4739, pages 62-73, 2002.
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Boosted ellipsoid ARTMAP. Anagnostopoulos, G. C.; Georgiopoulos, M.; Verzi, S. J.; and Heileman, G. L. In Proc. SPIE 4739, Applications and Science of Computational Intelligence V, volume 4739, pages 74-85, 2002.
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Fuzzy ART and Fuzzy ARTMAP with adaptively weighted distances. Charalampidis, D.; Anagnostopoulos, G. C.; Georgiopoulos, M.; and Kasparis, T. In Proc. SPIE 4739, Applications and Science of Computational Intelligence V, volume 4739, pages 86-97, 2002.
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Off-line structural risk minimization and BARTMAP-S. Verzi, S.; Heileman, G.; Georgiopoulos, M.; and Anagnostopoulos, G. C. In Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on, volume 3, pages 2533-2538, 2002.
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Tissue classification through analysis of gene expression data using a new family of ART architectures. Xu, R.; Anagnostopoulos, G. C.; and Wunsch, D. In Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on, volume 1, pages 300-304, 2002.
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  2001 (8)
Ellipsoid ART and ARTMAP for incremental clustering and classification. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on, volume 2, pages 1221-1226 vol.2, 2001.
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New geometric concepts in fuzzy-ART and fuzzy-ARTMAP: category regions. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on, volume 1, pages 32-37 vol.1, 2001.
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Novel Approaches in Adaptive Resonance Theory for Machine Learning. Anagnostopoulos, G. C. Ph.D. Thesis, University of Central Florida, Orlando, FL, USA, 2001. AAI3013900
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New geometrical perspective of fuzzy ART and fuzzy ARTMAP learning. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, volume 4390, pages 22-32, 2001.
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Ellipsoid ART and ARTMAP for incremental unsupervised and supervised learning. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, volume 4390, pages 293-304, 2001.
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Overtraining in fuzzy ARTMAP: Myth or reality?. Georgiopoulos, M.; Koufakou, A; Anagnostopoulos, G. C.; and Kasparis, T. In Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on, volume 2, pages 1186-1190, 2001.
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Cross-validation in fuzzy ARTMAP neural networks for large sample classification problems. Georgiopoulos, M.; Koufakou, A.; Anagnostopoulos, G. C.; and Kasparis, T. In Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, volume 4390, pages 1-11, 2001.
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Cross-validation in Fuzzy ARTMAP for Large Databases. Koufakou, A.; Georgiopoulos, M.; Anagnostopoulos, G. C.; and Kasparis, T. Neural Networks, 14(9): 1279--1291. November 2001.
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  2000 (2)
Hypersphere ART and ARTMAP for unsupervised and supervised, incremental learning. Anagnostopoulos, G. C.; and Georgiopoulos, M. In Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on, volume 6, pages 59-64 vol.6, 2000.
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Classification of noisy patterns using ARTMAP-based neural networks. Charalampidis, D.; Anagnostopoulos, G. C.; Kasparis, T.; and Georgiopoulos, M. In Proc. SPIE 4041, Visual Information Processing IX, volume 4041, pages 2-13, 2000.
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  1997 (1)
Ensembles of hybrid intelligent experts: extending the power of optimal linear combiners. Anagnostopoulos, G. C.; Georgiopoulos, M.; Nickerson, D.; and Bebis, G. In Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on, volume 2, pages 1350-1355 vol.2, Oct 1997.
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  1994 (1)
Non-linear optimization: artificial neural network solution techniques applied to the optimum linear feedback control of linear discrete-time dynamic systems. Economou, G.; Anagnostopoulos, G. C.; Theodosiou, D. T.; Stouraitis, T.; and Goutis, C. In EUROMICRO 94. System Architecture and Integration. Proceedings of the 20th EUROMICRO Conference., pages 637-643, Sep 1994.
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IFSAR Processing Using Variational Calculus. Sartor, K.; Tenali, G. B.; Peter, A. M.; Allen, J. D.; and Rahmes, M. American Society for Photogrammetry and Remote Sensing (ASPRS), . .
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Wavelet based density estimation for multidimensional streaming data. Weinand, D.; Nyengele, G.; Moyou, M.; and Peter, A. M. . .
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Functional Data Classification by Discriminative Interpolation with Features. Haber, R.; Rangarajan, A.; Mijatovic, N.; Smith, A. O.; and Peter, A. M. . .
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Room 240 AD, Orange County Convention Center Moderators: Andrew C. Novick, Cleveland, OH. Fujikawa, K.; Sasaki, M.; Aoyama, T.; Anton, P.; Kirchner, H.; Stief, C.; Jarrett, W.; Gershbaum, D.; Schnapp, D. S; Smith, A. D; and others . .
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