Index for oomm

Oomman, B.J. Co Author Listing * Geometrical Approach to Polygonal Dissimilarity and Shape Matching, A

Oommen, B.J.[B. John] Co Author Listing * email: Oommen, B.J.[B. John]: oommen AT scs carleton ca
* Anti-Bayesian parametric pattern classification using order statistics criteria for some members of the exponential family
* Breaking substitution cyphers using stochastic automata
* Chaotic Pattern Recognition: The Spectrum of Properties of the Adachi Neural Network
* Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction
* Continuous and Discretized Pursuit Learning Schemes: Various Algorithms and Their Comparison
* Corrigendum to three papers that deal with 'Anti'-Bayesian Pattern Recognition [Pattern Recognition]
* Determining stochastic dependence for normally distributed vectors using the chi-squared metric
* Discrete Vector Quantization for Arbitrary Distance Function Estimation
* Enhanced layered segment trees: a pragmatic data structure for real-time processing of geometric objects
* Enhancing prototype reduction schemes with LVQ3-type algorithms
* Formal Theory for Optimal and Information Theoretic Syntactic Pattern Recognition, A
* fundamental theory of optimal Anti-Bayesian parametric pattern classification using order statistics criteria, The
* Moment-Preserving Piecewise-Linear Approximations of Signals and Images
* Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes
* Multinomial Sequence Based Estimation Using Contiguous Subsequences of Length Three
* Noisy Substring Matching Problem, The
* Normalized String Editing Problem Revisited, The
* Novel Border Identification Algorithm Based on an Anti-Bayesian Paradigm, A
* Novel Strategy for Solving the Stochastic Point Location Problem Using a Hierarchical Searching Scheme, A
* On Achieving Near-Optimal Anti-Bayesian Order Statistics-Based Classification for Asymmetric Exponential Distributions
* On achieving semi-supervised pattern recognition by utilizing tree-based SOMs
* On Optimal Pairwise Linear Classifiers for Normal Distributions: The D-Dimensional Case
* On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case
* On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes
* On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes
* On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments
* On Terrain Model Acquisition by a Point Robot Amidst Polyhedral Obstacles
* On the classification of dynamical data streams using novel Anti-Bayesian techniques
* On the estimation of independent binomial random variables using occurrence and sequential information
* On the Pattern Recognition of Noisy Subsequence Trees
* On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables
* On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods
* On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures
* On using prototype reduction schemes to optimize dissimilarity-based classification
* On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods
* On using prototype reduction schemes to optimize locally linear reconstruction methods
* On using the chi-squared metric for determining stochastic dependence
* On Utilizing Search Methods to Select Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers
* Optimal Anti-Bayesian Parametric Pattern Classification for the Exponential Family Using Order Statistics Criteria
* Optimal anti-bayesian Parametric Pattern Classification Using Order Statistics Criteria
* Order statistics-based parametric classification for multi-dimensional distributions
* Pattern-Recognition of Strings with Substitutions, Insertions, Deletions and Generalized Transposition
* Peptide classification using optimal and information theoretic syntactic modeling
* Probabilistic Syntactic Pattern Recognition Involving Traditional and Generalized Transposition Errors
* Prototype reduction schemes applicable for non-stationary data sets
* Recognition of Noisy Subsequences Using Constrained Edit Distances
* Recognizing sources of random strings
* Robot Navigation in Unknown Terrain Using Learned Visibility Graphs. Part I: The Disjoint Convex Obstacle Case
* Scale Preserving Smoothing of Polygons
* Self-organizing maps whose topologies can be learned with adaptive binary search trees using conditional rotations
* Spelling Correction Using Probabilistic Methods
* Stochastic discretized learning-based weak estimation: A novel estimation method for non-stationary environments
* Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments
Includes: Oommen, B.J.[B. John] Oommen, B.J.
54 for Oommen, B.J.

Oommen, J.B.[John B.] Co Author Listing * Modeling Inaccurate Perception: Desynchronization Issues of a Chaotic Pattern Recognition Neural Network
* Numerical Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation

Oommen, T.[Thomas] Co Author Listing * Effect of Label Noise on the Machine-Learned Classification of Earthquake Damage
* Evidence of Instability in Previously-Mapped Landslides as Measured Using GPS, Optical, and SAR Data between 2007 and 2017: A Case Study in the Portuguese Bend Landslide Complex, California
* Post-Eruption Deformation Processes Measured Using ALOS-1 and UAVSAR InSAR at Pacaya Volcano, Guatemala

Index for "o"

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