M. Rizki

发表

M. Rizki, M. Conrad, 1986 .

Evolve III: a discrete events model of an evolutionary ecosystem.

M. Rizki, M. Conrad, Michael Conrad, 1985, Bio Systems.

Manifold Transfer Subspace Learning ( MTSL ) for High Dimensional Data — Applications to Handwritten Digits and Health Informatics

M. Rizki, M. Raymer, V. Velten, 2017 .

Changes in volatile compounds of mouse urine as it ages: Their interactions with water and urinary proteins

Claude C. Grigsby, M. Rizki, G. Preti, 2013, Physiology & Behavior.

Artificial worlds modeling of biological systems: an introduction to the special issue.

M. Rizki, M. Conrad, 1989, Bio Systems.

E-Net: Evolutionary neural network synthesis

Louis A. Tamburino, Mateen M. Rizki, Devert Wicker, 2002, Neurocomputing.

Differential binding between volatile ligands and major urinary proteins due to genetic variation in mice

Claude C. Grigsby, M. Rizki, G. Preti, 2012, Physiology & Behavior.

Manifold and transfer subspace learning for cross-domain vehicle recognition in dynamic systems

Mateen M. Rizki, Olga Mendoza-Schrock, Vincent J. Velten, 2015, 2015 18th International Conference on Information Fusion (Fusion).

Exploring EO vehicle recognition performance using manifolds as a function of lighting condition variability

John C. Gallagher, Michael L. Raymer, Edmund G. Zelnio, 2015, Defense + Security Symposium.

Electro-optical seasonal weather and gender data collection

Olga Mendoza-Schrock, Mateen Rizki, Ryan McCoppin, 2013, Defense, Security, and Sensing.

Differential profiling of volatile organic compound biomarker signatures utilizing a logical statistical filter-set and novel hybrid evolutionary classifiers

Ryan M. Kramer, Claude C. Grigsby, Claude C. Grigsby, 2012, Defense + Commercial Sensing.

HELPR: HYBRID EVOLUTIONARY LEARNING FOR PATTERN RECOGNITION

Mateen M. Rizki, L. A. Tamburino, M. Rizki, 2005 .

Multi-resolution feature extraction from Gabor filtered images

Mateen M. Rizki, Michael A. Zmuda, L. A. Tamburino, 1993, Proceedings of the IEEE 1993 National Aerospace and Electronics Conference-NAECON 1993.

Feature extraction using morphological analysis of multiresolution gray-scale images

Louis A. Tamburino, Mateen M. Rizki, Michael A. Zmuda, 1992, Defense, Security, and Sensing.

Performance-driven autonomous design of pattern-recognition systems

Louis A. Tamburino, Mateen M. Rizki, M. Rizki, 1992, Appl. Artif. Intell..

Target classification using morphological features

Mateen M. Rizki, Michael A. Zmuda, L. A. Tamburino, 2004, SPIE Defense + Commercial Sensing.

Hybrid evolutionary learning for synthesizing multi-class pattern recognition systems

Louis A. Tamburino, Mateen M. Rizki, Michael A. Zmuda, 2003, Appl. Soft Comput..

Evolving pattern recognition systems

Louis A. Tamburino, Mateen M. Rizki, Michael A. Zmuda, 2002, IEEE Trans. Evol. Comput..

The Multi-Tiered Tournament Selection for evolutionary neural network synthesis

Mateen M. Rizki, L. A. Tamburino, D. Wicker, 2000, 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No.00.

Generating Pattern- Recognition Systems Using Evolutionary Learning

Louis A. Tamburino, Mateen M. Rizki, Michael A. Zmuda, 1995, IEEE Expert.

A Hybrid Evolutionary Learining System for Synthesizing Neural Network Pattern Recognition Systems

Louis A. Tamburino, Mateen M. Rizki, Devert Wicker, 1998, Evolutionary Programming.

Manifold Transfer Subspace Learning (MTSL) for Applications in Aided Target Recognition

Mateen M. Rizki, Olga Mendoza-Schrock, Vincent J. Velten, 2017, Int. J. Monit. Surveillance Technol. Res..

Metabolite differentiation and discovery lab (MeDDL): a new tool for biomarker discovery and mass spectral visualization.

Claude C. Grigsby, Claude C Grigsby, M. Rizki, 2010, Analytical chemistry.

Memorial tribute to Dr. Michael Conrad

Robert G. Reynolds, David B. Fogel, Mateen M. Rizki, 2001, IEEE Trans. Evol. Comput..

Computational illustration of the bootstrap effect.

M Conrad, M. Rizki, M. Conrad, 1980, Bio Systems.

Feature and Prototype Evolution for Nearest Neighbor Classification of Web Documents

Michelle Cheatham, Mateen M. Rizki, M. Rizki, 2006, Third International Conference on Information Technology: New Generations (ITNG'06).

The artificial worlds approach to emergent evolution.

M Conrad, M. Rizki, M. Conrad, 1989, Bio Systems.

Vehicle classification for civilian and non-civilian applications: A survey

Olga Mendoza-Schrock, Mateen Rizki, Nikolas Bourbakis, 2014, NAECON 2014 - IEEE National Aerospace and Electronics Conference.

Evolutionary Optimization of Gaussian Windowing Functions for Data Preprocessing

Louis A. Tamburino, Ricardo Gutierrez-Osuna, Mateen M. Rizki, 2003, Int. J. Artif. Intell. Tools.

An evolutionary learning system for synthesizing complex morphological filters

Louis A. Tamburino, Mateen M. Rizki, Michael A. Zmuda, 1996, IEEE Trans. Syst. Man Cybern. Part B.

Automatic generation of morphological sequences

Mateen M. Rizki, Michael A. Zmuda, L. A. Tamburino, 1992, Optics & Photonics.

Changes in volatile compounds of human urine as it ages: their interaction with water.

Claude C. Grigsby, M. Rizki, G. Preti, 2013, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

Model-Based Simulation Architecture

Jerzy W. Rozenblit, Mateen M. Rizki, Peter C. Breedveld, 1984 .

Learning from a random player using the reference neuron model

G. Schleis, M. Rizki, M. Rizki, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).