*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

* Enhancing the Prediction of Lung Cancer Survival Rates Using 2d Features from 3d Scans

* 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.

55 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** * Characterizing Soil Stiffness Using Thermal Remote Sensing and Machine Learning

* 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

* Utilizing Hyperspectral Remote Sensing for Soil Gradation

Last update:16-Oct-21 13:40:16

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