Index for oja_

Oja, E.[Erkki] Co Author Listing * ALSM algorithm: An improved subspace method of classification, The
* Class-confidence critic combining
* Comparison of Techniques for Content-based Image Retrieval
* Comparison of X2 and K Statistics in Finding Signal and Picture Periodicity
* Comparisons of Probabilistic and Non-Probabilistic Hough Transforms
* Controlling On-line Adaptation of a Prototype-based Classifier for Handwritten Characters
* Cooccurrence Map: Quantizing Multidimensional Texture Histograms
* Density Function Interpretation of Subspace Cassification Methods
* Detecting Texture Periodicity from the Cooccurrence Matrix
* Distortion Tolerant Pattern-Recognition Based on Self-Organizing Feature-Extraction
* Entropy-based measures for clustering and SOM topology preservation applied to content-based image indexing and retrieval
* Experiments with adaptation strategies for a prototype-based recognition system for isolated handwritten characters
* Further Developments on RHT: Basic Mechanisms, Algorithms, and Computational Complexities
* Houghtool: A Software Package for the Use of the Hough Transform
* Image Feature Extraction and Denoising by Sparse Coding
* Image Feature Extraction by Sparse Coding and Independent Component Analysis
* Improving cluster analysis by co-initializations
* Learning Subspace Classifiers and Error Corrective Feature Extraction
* Learning the Information Divergence
* Methods for adaptive combination of classifiers with application to recognition of handwritten characters
* Multiplicative Updates for Learning with Stochastic Matrices
* Neural and Statistical Classifiers: Taxonomy and Two Case-Studies
* Neural Network and Statistical Perspectives of Classification
* Neural networks, principal components, and subspace
* New Curve Detection Method: Randomized Hough Transform (RHT), A
* Parametric Projection Filter for Image and Signal Restoration
* PicSOM: A Framework for Content-Based Image Database Retrieval Using Self-Organizing Maps
* PicSOM: Content-Based Image Retrieval with Self-Organizing Maps
* Principal components, minor components, and linear neural networks
* Probabilistic and Nonprobabilistic Hough Transforms: Overview and Comparisons
* Projective Nonnegative Matrix Factorization for Image Compression and Feature Extraction
* Quadratic nonnegative matrix factorization
* Randomized Hough transform (RHT)
* Randomized Hough Transform (RHT): Basic Mechanisms, Algorithms, and Computational Complexities
* Randomized Hough Transform Applied to Translational and Rotational Motion Analysis
* Reduced Multidimensional Cooccurrence Histograms in Texture Classification
* Reduced Multidimensional Histograms in Color Texture Description
* Reduced Multidimensional Texture Histograms
* Rejection methods for an adaptive committee classifier
* Self-Organising Maps as a Relevance Feedback Technique in Content-Based Image Retrieval
* simplified neuron model as a principal component analyzer, A
* Speeding up on-line recognition of handwritten characters by pruning the prototype set
* Statistical Shape Features for Content-Based Image Retrieval
* Statistical Shape Features in Content-based Image Retrieval
* Task-Based User Evaluation of Content-Based Image Database Browsing Systems
* Texture Classification with Single and Multiresolution Cooccurrence Maps
* Texture discrimination with multidimensional distributions of signed gray-level differences
* Unsupervised and supervised classifications by rival penalized competitive learning
* Use of Image Subset Features in Image Retrieval with Self-Organizing Maps
* Using MPEG-7 Descriptors in Image Retrieval with Self-Organizing Maps
* Wavelets And Natural Image Statistics
Includes: Oja, E.[Erkki] Oja, E.
51 for Oja, E.

Oja, H. Co Author Listing * Asymptotic and Bootstrap Tests for the Dimension of the Non-Gaussian Subspace
* Classification Based on Hybridization of Parametric and Nonparametric Classifiers
Includes: Oja, H. Oja, H.[Hannu]

Oja, T.[Tonu] Co Author Listing * Implications of Field Worker Characteristics and Landscape Heterogeneity for Classification Correctness and the Completeness of Topographical Mapping, The
Includes: Oja, T.[Tonu] Oja, T.[Tõnu]

Index for "o"


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