Robert P. W. Duin

发表

Model Based Recognition of 3D Objects From Single 2D Images

Etienne P. Romsom, Robert P. W. Duin, R. Duin, 1989, IAS.

Feature Shaving for Spectroscopic Data

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2004, SSPR/SPR.

Fast kNN mode seeking clustering applied to active learning pdf

Robert P. W. Duin, Sergey Verzakov, 2017, ArXiv.

The Science of Pattern Recognition. Achievements and Perspectives

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2007, Challenges for Computational Intelligence.

Support Vector Data Description

Robert P. W. Duin, David M. J. Tax, D. Tax, 2004, Machine Learning.

Uncertainty sampling methods for one-class classifiers

Robert P. W. Duin, Piotr Juszczak, P. Juszczak, 2003 .

Learned from Neural Networks

Robert P. W. Duin, R. Duin, 2000 .

Learning from a Test Set

Robert P. W. Duin, Piotr Juszczak, 2005, CORES.

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2002, Pattern Recognit. Lett..

Robert P. W. Duin, Elzbieta Pekalska, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Classifying Three-way Seismic Volcanic Data by Dissimilarity Representation

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2010, 2010 20th International Conference on Pattern Recognition.

Decision templates for multiple classifier fusion: an experimental comparison

James C. Bezdek, Robert P. W. Duin, Ludmila I. Kuncheva, 2001, Pattern Recognit..

Neural network experiences between perceptrons and support vectors

Robert P. W. Duin, Dick de Ridder, R. Duin, 1997, BMVC.

Selective sampling based on the variation in label assignments

Robert P. W. Duin, Piotr Juszczak, 2004, ICPR 2004.

Classifier Conditional Posterior Probabilities

Robert P. W. Duin, David M. J. Tax, D. Tax, 1998, SSPR/SPR.

Towards Cluster-Based Prototype Sets for Classification in the Dissimilarity Space

Robert P. W. Duin, Mauricio Orozco-Alzate, Edel B. García Reyes, 2013, CIARP.

Random Subspace Method in Text Categorization

Mohamed S. Kamel, Mehrdad J. Gangeh, Robert P. W. Duin, 2010, 2010 20th International Conference on Pattern Recognition.

AUTOMATIC PATTERN RECOGNITION BY SIMILARITY REPRESENTATIONS - A NOVEL APPROACH

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2001 .

A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection

Yan Li, Robert P. W. Duin, Mauricio Orozco-Alzate, 2016, CIARP.

Selecting feature lines in generalized dissimilarity representations for pattern recognition

Robert P. W. Duin, Mauricio Orozco-Alzate, Edel B. García Reyes, 2013, Digit. Signal Process..

Superlearning and neural network magic

Robert P. W. Duin, R. Duin, 1994, Pattern Recognit. Lett..

Minimum spanning tree based one-class classifier

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, 2009, Neurocomputing.

Data description in subspaces

Robert P. W. Duin, David M. J. Tax, D. Tax, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Subclass Problem-Dependent Design for Error-Correcting Output Codes

Sergio Escalera, Petia Radeva, Robert P. W. Duin, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Missing Values in Dissimilarity-Based Classification of Multi-way Data

Robert P. W. Duin, Diana Porro-Muñoz, Isneri Talavera-Bustamante, 2013, CIARP.

Semi-supervised hyperspectral pixel classification using interactive labeling

Robert P. W. Duin, Pedro García-Sevilla, Olga Rajadell, 2011, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Learning procedure for the recognition of 3-D objects from 2-D images

Robert P. W. Duin, Johannes Buurman, Mischa Bart, 1991, Other Conferences.

The Tangent Kernel Approach to Illumination-Robust Texture Classification

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2005, SCIA.

On refining dissimilarity matrices for an improved NN learning

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2008, 2008 19th International Conference on Pattern Recognition.

Investigating redundancy in feed-forward neural classifiers

Robert P. W. Duin, Aarnoud Hoekstra, 1997, Pattern Recognit. Lett..

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2010, SSPR/SPR.

The combining classifier: to train or not to train?

Robert P. W. Duin, R. Duin, 2002, Object recognition supported by user interaction for service robots.

On the speed of training networks with correlated features

Robert P. W. Duin, R.R.N. Bakker, M. A. Kraaijveld, 1993, IEEE International Conference on Neural Networks.

Comments on "Independence, Measurement Complexity, and Classification Performance"

Robert P. W. Duin, 1977, IEEE Trans. Syst. Man Cybern..

Continuous Multi-way Shape Measure for Dissimilarity Representation

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2012, CIARP.

SEDMI: Saliency based edge detection in multispectral images

Robert P. W. Duin, Pavel Paclík, Marco Loog, 2011, Image Vis. Comput..

Relational discriminant analysis

Robert P. W. Duin, Elzbieta Pekalska, Dick de Ridder, 1999, Pattern Recognit. Lett..

Robert P. W. Duin, R. Duin, 2015, Pattern Recognit. Lett..

Precision-recall operating characteristic (P-ROC) curves in imprecise environments

Robert P. W. Duin, Pavel Paclík, Thomas Landgrebe, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Learning with General Proximity Measures

Robert P. W. Duin, Elzbieta Pekalska, 2006, PRIS.

Feedforward neural networks with random weights

Robert P. W. Duin, M. A. Kraaijveld, W. F. Schmidt, 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.

Support objects for domain approximation

Robert P. W. Duin, Alexander Ypma, 1998 .

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2011, Computación y Sistemas.

Dimensionality Reduction by Canonical Contextual Correlation Projections

Robert P. W. Duin, Bram van Ginneken, Marco Loog, 2004, ECCV.

Non-Euclidean Dissimilarities: Causes and Informativeness

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2010, SSPR/SPR.

Pairwise feature evaluation for constructing reduced representations

Robert P. W. Duin, Elzbieta Pekalska, Carmen Lai, 2007, Pattern Analysis and Applications.

Linear dimensionality reduction via a heteroscedastic extension of LDA: the Chernoff criterion

Robert P. W. Duin, Marco Loog, R. Duin, 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Health Monitoring with Learning Methods

Robert P. W. Duin, Alexander Ypma, Co Melissant, 2001, ICANN.

Statistical Pattern Recognition: A Review

Anil K. Jain, Robert P. W. Duin, Jianchang Mao, 2000, IEEE Trans. Pattern Anal. Mach. Intell..

Component-based discriminative classification for hidden Markov models

Robert P. W. Duin, Manuele Bicego, Elzbieta Pekalska, 2009, Pattern Recognit..

Wan-Jui Lee, Robert P. W. Duin, Marco Loog, 2011, SIMBAD.

Capacity of feedforward networks with shared weights

Robert P. W. Duin, M. A. Kraaijveld, 1992, Defense, Security, and Sensing.

Parameter Estimation and State Estimation: An Engineering Approach using MATLAB

Robert P. W. Duin, Ferdinand van der Heijden, David M. J. Tax, 2004 .

Domain based classification pdf

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2016, ArXiv.

A study on design of object sorting algorithms in the industrial application using hyperspectral imaging

Robert P. W. Duin, Pavel Paclík, Raimund Leitner, 2006, Journal of Real-Time Image Processing.

A note on core research issues for statistical pattern recognition

Fabio Roli, Robert P. W. Duin, Dick de Ridder, 2002, Pattern Recognit. Lett..

Segmentation of multi-spectral images using the combined classifier approach

Geert M. P. van Kempen, Robert P. W. Duin, Pavel Paclík, 2003, Image Vis. Comput..

Classifiers in almost empty spaces

Robert P. W. Duin, R. Duin, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Bridging Structure and Feature Representations in Graph Matching

Wan-Jui Lee, Robert P. W. Duin, Marco Loog, 2012, Int. J. Pattern Recognit. Artif. Intell..

SMD position measurement by a Kohonen network compared with image processing

Robert P. W. Duin, Edwin Th. G. Hoek, R. Duin, 1995, CAIP.

Linear model combining by optimizing the Area under the ROC curve

Robert P. W. Duin, David M. J. Tax, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

K-nearest Neighbors Directed Noise Injection in Multilayer Perceptron Training

Robert P. W. Duin, Sarunas Raudys, Marina Skurichina, 2000, IEEE Trans. Neural Networks Learn. Syst..

Introduction to Pattern Recognition1

Anil K. Jain, Robert P. W. Duin, R. Duin, 2007 .

A Clustering Based Method for Edge Detection in Hyperspectral Images

Robert P. W. Duin, Pavel Paclík, Raimund Leitner, 2009, SCIA.

On the evaluation of independent binary features (Corresp.)

Robert P. W. Duin, Chris E. van Haersma Buma, L. Roosma, 1978, IEEE Trans. Inf. Theory.

Pump Failure Detection Using Support Vector Data Descriptions

Robert P. W. Duin, David M. J. Tax, Alexander Ypma, 1999, IDA.

On the Application of Neural Networks to Non-Linear Image Processing Tasks

Robert P. W. Duin, Lucas J. van Vliet, Piet W. Verbeek, 1998, ICONIP.

Support vector domain description

Robert P. W. Duin, David M. J. Tax, D. Tax, 1999, Pattern Recognit. Lett..

Detection and Classification

Robert P. W. Duin, David M. J. Tax, F. van der Heijden, 2005 .

Generalization capabilities of minimal kernel-based networks

Robert P. W. Duin, M. A. Kraaijveld, R. Duin, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Early diagnosis of dementia based on intersubject whole-brain dissimilarities

Stefan Klein, Robert P. W. Duin, Marleen de Bruijne, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Non-Euclidean Problems in Pattern Recognition Related to Human Expert Knowledge

Robert P. W. Duin, 2010, ICEIS.

Prototype Selection for Dissimilarity Representation by a Genetic Algorithm

Robert P. W. Duin, Mauricio Orozco-Alzate, Edel B. García Reyes, 2010, 2010 20th International Conference on Pattern Recognition.

ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers

Robert P. W. Duin, Pavel Paclík, Carmen Lai, 2010, 2010 20th International Conference on Pattern Recognition.

An Evaluation of Intrinsic Dimensionality Estimators

Robert P. W. Duin, Peter J. Verveer, 1995, IEEE Trans. Pattern Anal. Mach. Intell..

Maximizing the area under the ROC curve by pairwise feature combination

Robert P. W. Duin, Claudio Marrocco, Francesco Tortorella, 2008, Pattern Recognit..

Multi-class Classification in Image Analysis via Error-Correcting Output Codes

Sergio Escalera, Petia Radeva, Robert P. W. Duin, 2011 .

Wan-Jui Lee, Lauge Sørensen, Robert P. W. Duin, 2010, SSPR/SPR.

Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance

Robert P. W. Duin, Sang-Woon Kim, Manuele Bicego, 2014, S+SSPR.

An experimental comparison of neural classifiers with ‘traditional’ classifiers

Robert P. W. Duin, W. F. Schmidt, D. F. Levelt, 1994 .

A generalization of dissimilarity representations using feature lines and feature planes

Robert P. W. Duin, Germán Castellanos-Domínguez, Mauricio Orozco-Alzate, 2009, Pattern Recognit. Lett..

Kernel Combination Versus Classifier Combination

Wan-Jui Lee, Robert P. W. Duin, Sergey Verzakov, 2007, MCS.

Bagging for linear classifiers

Robert P. W. Duin, Marina Skurichina, R. Duin, 1998, Pattern Recognit..

On Using a Pre-clustering Technique to Optimize LDA-Based Classifiers for Appearance-Based Face Recognition

Robert P. W. Duin, Sang-Woon Kim, 2007, CIARP.

The adaptive subspace map for texture segmentation

Josef Kittler, Robert P. W. Duin, Dick de Ridder, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Pattern recognition as a statistical method for analyzing the confidence level in the identification of objects

Robert P. W. Duin, M. De Bruin, P. J. M. Korthoven, 1973 .

Using two-class classifiers for multiclass classification

Robert P. W. Duin, David M. J. Tax, 2002, Object recognition supported by user interaction for service robots.

Novelty Detection Using Self-Organizing Maps

Robert P. W. Duin, Alexander Ypma, A. Ypma, 1997, ICONIP.

Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems

Wan-Jui Lee, Horst Bunke, Robert P. W. Duin, 2010, MCS.

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2011, CIARP.

Structural, Syntactic, And Statistical Pattern Recognition: Joint Iapr International Workshops, Sspr 2004 And Spr 2004, Lisbon, Portugal, August 18-20 ... oceedings (Lecture Notes in Computer Science)

Robert P. W. Duin, Terry Caelli, Dick de Ridder, 2004 .

Domain Based LDA and QDA

Robert P. W. Duin, Serguei Verzakov, David M. J. Tax, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Edge Detection in Hyperspectral Imaging: Multivariate Statistical Approaches

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2006, SSPR/SPR.

On Improving Dissimilarity-Based Classifications Using a Statistical Similarity Measure

Robert P. W. Duin, Sang-Woon Kim, R. Duin, 2010, CIARP.

Generalizing Dissimilarity Representations Using Feature Lines

Robert P. W. Duin, Germán Castellanos-Domínguez, Mauricio Orozco-Alzate, 2007, CIARP.

Limits on the majority vote accuracy in classifier fusion

Robert P. W. Duin, Ludmila I. Kuncheva, Christopher J. Whitaker, 2003, Pattern Analysis & Applications.

Combining Fisher Linear Discriminants for Dissimilarity Representations

Robert P. W. Duin, Elzbieta Pekalska, Marina Skurichina, 2000, Multiple Classifier Systems.

A Combine-Correct-Combine Scheme for Optimizing Dissimilarity-Based Classifiers

Robert P. W. Duin, Sang-Woon Kim, 2009, CIARP.

Fast percentile filtering

Robert P. W. Duin, R. Zeelen, H. Haringa, 1986, Pattern Recognit. Lett..

Outliers and data descriptions

Robert P. W. Duin, David M. J. Tax, D. Tax, 2001 .

Classification of three-way data by the dissimilarity representation

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2011, Signal Process..

Robert P. W. Duin, Cesar G. Castellanos, Mauricio Orozco, 2006 .

Cost-Based Classifier Evaluation for Imbalanced Problems

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2004, SSPR/SPR.

Variance estimation for two-class and multi-class ROC analysis using operating point averaging

Robert P. W. Duin, Pavel Paclík, Jana Novovicová, 2008, 2008 19th International Conference on Pattern Recognition.

Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation

Josef Kittler, Robert P. W. Duin, Dick de Ridder, 2000, BMVC.

Multiple-instance learning as a classifier combining problem

Robert P. W. Duin, Marco Loog, David M. J. Tax, 2013, Pattern Recognit..

Structural Inference of Sensor-Based Measurements

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2006, SSPR/SPR.

Growing a multi-class classifier with a reject option

Robert P. W. Duin, David M. J. Tax, D. Tax, 2008, Pattern Recognit. Lett..

Experiments with a featureless approach to pattern recognition

Robert P. W. Duin, David M. J. Tax, Dick de Ridder, 1997, Pattern Recognit. Lett..

STATISTICAL PATTERN RECOGNITION

Robert P. W. Duin, David M. J. Tax, D. Tax, 2005 .

Robert P. W. Duin, Sang-Woon Kim, R. Duin, 2011, CIARP.

Texture Description by Independent Components

Josef Kittler, Robert P. W. Duin, Dick de Ridder, 2002, SSPR/SPR.

Bagging, Boosting and the Random Subspace Method for Linear Classifiers

Robert P. W. Duin, Marina Skurichina, R. Duin, 2002, Pattern Analysis & Applications.

A study on semi-supervised dissimilarity representation

Robert P. W. Duin, Marco Loog, Viet Cuong Dinh, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy

Robert P. W. Duin, Ludmila I. Kuncheva, Marina Skurichina, 2002, Multiple Classifier Systems.

Non-Euclidean or Non-metric Measures Can Be Informative

Horst Bunke, Robert P. W. Duin, Elzbieta Pekalska, 2006, SSPR/SPR.

A Hardware Design For Fast 2-D Percentile Filtering

Robert P. W. Duin, R. Zeelen, H. Haringa, 1986, Other Conferences.

The effective capacity of multilayer feedforward network classifiers

Robert P. W. Duin, Martin A. Kraaijveld, R. Duin, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

The Similarity Between Dissimilarities

Robert P. W. Duin, David M. J. Tax, Veronika Cheplygina, 2016, S+SSPR.

The mean recognition performance for independent distributions (Corresp.)

Robert P. W. Duin, R. Duin, 1978, IEEE Trans. Inf. Theory.

Almost autonomous training of mixtures of principal component analyzers

Robert P. W. Duin, Volkan Atalay, Dick de Ridder, 2004, Pattern Recognit. Lett..

Robert P. W. Duin, Pavel Paclík, Jana Novovicová, 2006, 18th International Conference on Pattern Recognition (ICPR'06).

Optimal Mean-Precision Classifier

Robert P. W. Duin, Marco Loog, David M. J. Tax, 2009, MCS.

Mode Seeking Clustering by KNN and Mean Shift Evaluated

Ana L. N. Fred, Robert P. W. Duin, Elzbieta Pekalska, 2012, SSPR/SPR.

Robert P. W. Duin, Manuele Bicego, Umberto Castellani, 2010, ICPR 2010.

One-Class LP Classifiers for Dissimilarity Representations

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, 2002, NIPS.

Uniform Object Generation for Optimizing One-class Classifiers

Robert P. W. Duin, David M. J. Tax, D. Tax, 2002, J. Mach. Learn. Res..

Supervised localization of cell nuclei on TMA images

Robert P. W. Duin, Marco Loog, Alessandro Ibba, 2012, 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis.

Multi-class linear feature extraction by nonlinear PCA

Robert P. W. Duin, Reinhold Häb-Umbach, Marco Loog, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Prototype selection for finding efficient representations of dissimilarity data

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2002, Object recognition supported by user interaction for service robots.

Combining One-Class Classifiers

Robert P. W. Duin, David M. J. Tax, D. Tax, 2001, Multiple Classifier Systems.

Augmented Embedding of Dissimilarity Data into (Pseudo-)Euclidean Spaces

Robert P. W. Duin, Serguei Verzakov, Elzbieta Pekalska, 2006, SSPR/SPR.

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2005, Series in Machine Perception and Artificial Intelligence.

An experimental study on diversity for bagging and boosting with linear classifiers

Robert P. W. Duin, Ludmila I. Kuncheva, Marina Skurichina, 2002, Inf. Fusion.

An experimental study on combining Euclidean distances

Wan-Jui Lee, Robert P. W. Duin, Marco Loog, 2010, 2010 2nd International Workshop on Cognitive Information Processing.

A new measure for the effect of sharpening and smoothing filters on images

Robert P. W. Duin, Piet W. Verbeek, Ian T. Young, 1999 .

The Area under the ROC Curve as a Criterion for Clustering Evaluation

Ana L. N. Fred, Robert P. W. Duin, Helena Aidos, 2013, ICPRAM.

Technological Challenges in Defect Detection for Metal Strip; Pattern Recognition Algorithms

Robert P. W. Duin, Pieter Jonker, Dick de Ridder, 1999 .

Learning with General Proximity Measures (invited paper)

Ana L. N. Fred, Robert P. W. Duin, Elzbieta Pekalska, 2006 .

The Representation of Chemical Spectral Data for Classification

Robert P. W. Duin, Diana Porro-Muñoz, Isneri Talavera-Bustamante, 2009, CIARP.

Expected classification error of the Fisher linear classifier with pseudo-inverse covariance matrix

Robert P. W. Duin, Sarunas Raudys, S. Raudys, 1998, Pattern Recognit. Lett..

Stabilizing classifiers for very small sample sizes

Robert P. W. Duin, Marina Skurichina, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Automated Colorectal Cancer Diagnosis for Whole-Slice Histopathology

Robert P. W. Duin, Marco Loog, Habil Kalkan, 2012, MICCAI.

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2012, Pattern Recognit. Lett..

A Study on the Influence of Shape in Classifying Small Spectral Data Sets

Robert P. W. Duin, Diana Porro-Muñoz, Mauricio Orozco-Alzate, 2011, SIMBAD.

Improving Hyperspectral Pixel Classification With Unsupervised Training Data Selection

Robert P. W. Duin, Pedro García-Sevilla, Olga Rajadell, 2014, IEEE Geoscience and Remote Sensing Letters.

Effectiveness of Spectral Band Selection/Extraction Techniques for Spectral Data

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2006, SSPR/SPR.

Relational discriminant analysis and its large sample size problem

Robert P. W. Duin, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

Estimating the Reliability of Neural Network Classifications

Robert P. W. Duin, Aarnoud Hoekstra, Servaes A. Tholen, 1996, ICANN.

Classification of Volcano Events Observed by Multiple Seismic Stations

Robert P. W. Duin, Mauricio Orozco-Alzate, John Makario Londoño-Bonilla, 2010, 2010 20th International Conference on Pattern Recognition.

Transforming Strings to Vector Spaces Using Prototype Selection

Horst Bunke, Robert P. W. Duin, Elzbieta Pekalska, 2006, SSPR/SPR.

A Matlab Toolbox for Pattern Recognition

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, 2004 .

Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria

Robert P. W. Duin, Reinhold Häb-Umbach, Marco Loog, 2001, IEEE Trans. Pattern Anal. Mach. Intell..

Outlier Detection Using Ball Descriptions with Adjustable Metric

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, 2006, SSPR/SPR.

Appendix D: Discrete‐Time Dynamic Systems

Robert P. W. Duin, David M. J. Tax, D. de Ridder, 2005 .

Neural network initialization by combined classifiers

Robert P. W. Duin, Martijn van Breukelen, R. Duin, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

Evaluation method for an automatic map interpretation system for cadastral maps

Albert M. Vossepoel, Robert P. W. Duin, Rik D. T. Janssen, 1993, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93).

Recent submissions in linear dimensionality reduction and face recognition

Tin Kam Ho, Robert P. W. Duin, Marco Loog, 2006, Pattern Recognit. Lett..

Possibilities of Zero-Error Recognition by Dissimilarity Representations

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2002, PRIS.

Combining classifiers

Josef Kittler, Robert P. W. Duin, Mohamad Hatef, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Statistical Analysis of Gait Data to Assist Clinical Decision Making

Robert P. W. Duin, Nigar Sen Köktas, 2009, MCBR-CDS.

On the Informativeness of Asymmetric Dissimilarities (abstract)

Robert P. W. Duin, David M. J. Tax, Veronika Cheplygina, 2013, BNAIC 2013.

The economics of classification: error vs. complexity

Robert P. W. Duin, Elzbieta Pekalska, Dick de Ridder, 2002, Object recognition supported by user interaction for service robots.

On Combining Dissimilarity Representations

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2001, Multiple Classifier Systems.

On Backpropagation Learning of Edited Data Sets

Robert P. W. Duin, M. A. Kraaijveld, 1990 .

Combining multiple classifiers by averaging or by multiplying?

Josef Kittler, Robert P. W. Duin, David M. J. Tax, 2000, Pattern Recognit..

Optimising Two-Stage Recognition Systems

Robert P. W. Duin, Pavel Paclík, David M. J. Tax, 2005, Multiple Classifier Systems.

One-class and Multi-class classier combining for ill-dened problems

Robert P. W. Duin, David M. J. Tax, Colin M. Andrew, 2004 .

Four Scientific Approaches to Pattern Recognition

Robert P. W. Duin, R. Duin, 2001 .

Robust machine fault detection with independent component analysis and support vector data description

Robert P. W. Duin, David M. J. Tax, Alexander Ypma, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

Regularization by Adding Redundant Features

Robert P. W. Duin, Marina Skurichina, 1998, SSPR/SPR.

Building Road-Sign Classifiers Using a Trainable Similarity Measure

Robert P. W. Duin, Pavel Paclík, Jana Novovicová, 2006, IEEE Transactions on Intelligent Transportation Systems.

On the nonlinearity of pattern classifiers

Robert P. W. Duin, Aarnoud Hoekstra, R. Duin, 1996, Proceedings of 13th International Conference on Pattern Recognition.

Initializations, back-propagation and generalization of feed-forward classifiers

Robert P. W. Duin, M. A. Kraaijveld, W. F. Schmidt, 1993, IEEE International Conference on Neural Networks.

Feature-Based Dissimilarity Space Classification

Robert P. W. Duin, Elzbieta Pekalska, Marco Loog, 2010, ICPR Contests.

Dealing with a priori knowledge by fuzzy labels

Robert P. W. Duin, Frits T. Beukema toe Water, R. Duin, 1981, Pattern Recognit..

Featureless pattern classification

Robert P. W. Duin, David M. J. Tax, Dick de Ridder, 1998, Kybernetika.

Outlier Detection Using Classifier Instability

Robert P. W. Duin, David M. J. Tax, D. Tax, 1998, SSPR/SPR.

A multi-classifier for grading knee osteoarthritis using gait analysis

Robert P. W. Duin, Nese Yalabik, Nigar Sen Köktas, 2010, Pattern Recognit. Lett..

Data domain description using support vectors

Robert P. W. Duin, David M. J. Tax, D. Tax, 1999, ESANN.

A simplified extension of the Area under the ROC to the multiclass domain

Robert P. W. Duin, Thomas C. W. Landgrebe, 2006 .

An algorithm for benchmarking an SIMD pyramid with the Abingdon Cross

Robert P. W. Duin, Wouter B. Teeuw, 1990, Pattern Recognit. Lett..

Multi-class extensions of the GLDB feature extraction algorithm for spectral data

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

A Two-Stage Combined Classifier in Scale Space Texture Classification pdf

Mohamed S. Kamel, Mehrdad J. Gangeh, Robert P. W. Duin, 2012, ArXiv.

Neural networks applied to data analysis

Robert P. W. Duin, Aarnoud Hoekstra, M. A. Kraaijveld, 1998 .

Worked out Examples

Robert P. W. Duin, David M. J. Tax, D. de Ridder, 2005 .

Improving the Maximum-Likelihood Co-occurrence Classifier: A Study on Classification of Inhomogeneous Rock Images

Robert P. W. Duin, Serguei Verzakov, Pavel Paclík, 2005, SCIA.

On Combining Dissimilarity-Based Classifiers to Solve the Small Sample Size Problem for Appearance-Based Face Recognition

Robert P. W. Duin, Sang-Woon Kim, 2007, Canadian Conference on AI.

Appendix F: MATLAB Toolboxes Used

Robert P. W. Duin, David M. J. Tax, F. van der Heijden, 2005 .

A Study on Combining Sets of Differently Measured Dissimilarities

Wan-Jui Lee, Robert P. W. Duin, Alessandro Ibba, 2010, 2010 20th International Conference on Pattern Recognition.

Combining Feature Subsets in Feature Selection

Robert P. W. Duin, Marina Skurichina, 2005, Multiple Classifier Systems.

Dimensionality reduction of image features using the canonical contextual correlation projection

Robert P. W. Duin, Bram van Ginneken, Marco Loog, 2005, Pattern Recognit..

On Combining Classifiers

Jiri Matas, Josef Kittler, Robert P. W. Duin, 1998, IEEE Trans. Pattern Anal. Mach. Intell..

Integration of prior knowledge of measurement noise in kernel density classification

Marcel J. T. Reinders, Robert P. W. Duin, Dick de Ridder, 2008, Pattern Recognit..

Combining One-Class Classifiers to Classify Missing Data

Robert P. W. Duin, Piotr Juszczak, P. Juszczak, 2004, Multiple Classifier Systems.

Supervised Locally Linear Embedding

Matti Pietikäinen, Robert P. W. Duin, Dick de Ridder, 2003, ICANN.

A Fast Approach to Improve Classification Performance of ECOC Classification Systems

Robert P. W. Duin, Francesco Tortorella, David M. J. Tax, 2008, SSPR/SPR.

Sammon's mapping using neural networks: A comparison

Robert P. W. Duin, Dick de Ridder, 1997, Pattern Recognit. Lett..

Robert P. W. Duin, Pavel Paclík, R. Duin, 2003, Real Time Imaging.

Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis

Robert P. W. Duin, Thomas Landgrebe, R. Duin, 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Combining Accuracy and Prior Sensitivity for Classifier Design Under Prior Uncertainty

Robert P. W. Duin, Thomas Landgrebe, R. Duin, 2006, SSPR/SPR.

On Deriving the Second-Stage Training Set for Trainable Combiners

Robert P. W. Duin, Pavel Paclík, David M. J. Tax, 2005, Multiple Classifier Systems.

Multi-spectral video endoscopy system for the detection of cancerous tissue

Robert P. W. Duin, Marco Loog, Raimund Leitner, 2013, Pattern Recognit. Lett..

The MDF discrimination measure: Fisher in disguise

Max A. Viergever, Robert P. W. Duin, Marco Loog, 2004, Neural Networks.

Architectures for Multidimensional Low- and Intermediate Level Image Processing (Invited)

Robert P. W. Duin, Pieter P. Jonker, Erwin R. Komen, 1990, MVA.

Spirograph Theory: A Framework for Calculations on Digitized Straight Lines

Robert P. W. Duin, L. Dorst, R. Duin, 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Non-iterative Heteroscedastic Linear Dimension Reduction for Two-Class Data

Robert P. W. Duin, Marco Loog, R. Duin, 2002, SSPR/SPR.

Mapping an N N Image on P Processors

Robert P. W. Duin, Pieter P. Jonker, Wouter B. Teeuw, 1990, MVA.

An experimental study of one- and two-level classifier fusion for different sample sizes

Chun-Xia Zhang, Robert P. W. Duin, R. Duin, 2011, Pattern Recognit. Lett..

On Not Making Dissimilarities Euclidean

Horst Bunke, Robert P. W. Duin, Simon Günter, 2004, SSPR/SPR.

Handwritten digit recognition by combined classifiers

Robert P. W. Duin, David M. J. Tax, J. E. den Hartog, 1998, Kybernetika.

Pairwise Selection of Features and Prototypes

Robert P. W. Duin, Elzbieta Pekalska, Carmen Lai, 2005, CORES.

Spherical and Hyperbolic Embeddings of Data

Edwin R. Hancock, Robert P. W. Duin, Richard C. Wilson, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Non-Euclidean Dissimilarities: Causes, Embedding and Informativeness

Robert P. W. Duin, Elzbieta Pekalska, Marco Loog, 2013, Similarity-Based Pattern Analysis and Recognition.

A Labelled Graph Based Multiple Classifier System

Wan-Jui Lee, Robert P. W. Duin, 2009, MCS.

MULTI-SPECTRAL IMAGE SEGMENTATION ALGORITHM COMBINING SPATIAL AND SPECTRAL INFORMATION

Geert M. P. van Kempen, Robert P. W. Duin, Pavel Pacĺık, 2007 .

Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

Filiberto Pla, José Martínez Sotoca, Robert P. W. Duin, 2006, Pattern Recognit..

Robert P. W. Duin, Elzbieta Pekalska, Marina Skurichina, 2004, Multiple Classifier Systems.

The use of continuous variables for labeling objects

Robert P. W. Duin, 1982, Pattern Recognit. Lett..

Robert P. W. Duin, Michele Tansella, Manuele Bicego, 2010, 2010 First Workshop on Brain Decoding: Pattern Recognition Challenges in Neuroimaging.

Is independence good for combining classifiers?

Robert P. W. Duin, Ludmila I. Kuncheva, Christopher J. Whitaker, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Open Issues in Pattern Recognition

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2005, CORES.

The Adaptive Subspace Map for Image Description and Image Database Retrieval

Josef Kittler, Robert P. W. Duin, Dick de Ridder, 2000, SSPR/SPR.

A note on comparing classifiers

Robert P. W. Duin, R. Duin, 1996, Pattern Recognit. Lett..

Spectral Characterization of Volcanic Earthquakes at Nevado del Ruiz Volcano Using Spectral Band Selection/Extraction Techniques

Robert P. W. Duin, Mauricio Orozco-Alzate, Marina Skurichina, 2008, CIARP.

Generalized Augmentation of Multiple Kernels

Wan-Jui Lee, Robert P. W. Duin, Marco Loog, 2011, MCS.

Approximating the multiclass ROC by pairwise analysis

Robert P. W. Duin, Thomas Landgrebe, R. Duin, 2007, Pattern Recognit. Lett..

Automated classification of local patches in colon histopathology

Robert P. W. Duin, Marco Loog, Habil Kalkan, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

FIDOS: A generalized Fisher based feature extraction method for domain shift

Robert P. W. Duin, Marco Loog, Viet Cuong Dinh, 2013, Pattern Recognit..

Classification using High Order Dissimilarities in Non-euclidean Spaces

Ana L. N. Fred, Robert P. W. Duin, Helena Aidos, 2012, ICPRAM.

Further data exploration

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2005 .

Correction to 'The Mean Recognition performance for Independent Distribution'

Robert P. W. Duin, R. Duin, 1978, IEEE Trans. Inf. Theory.

Beyond Traditional Kernels: Classification in Two Dissimilarity-Based Representation Spaces

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Texture Segmentation Using the Mixtures of Principal Component Analyzers

Robert P. W. Duin, Volkan Atalay, Dick de Ridder, 2003, ISCIS.

Boosting in Linear Discriminant Analysis

Robert P. W. Duin, Marina Skurichina, 2000, Multiple Classifier Systems.

Computation of Concave Piecewise Linear Discriminant Functions Using Chebyshev Polynomials

Robert P. W. Duin, Chris E. van Haersma Buma, R. Duin, 1976, IEEE Transactions on Computers.

Selective Sampling Methods in One-Class Classification Problems

Robert P. W. Duin, Piotr Juszczak, P. Juszczak, 2003, ICANN.

Pattern Recognition as a Human Centered non-Euclidean Problem

Robert P. W. Duin, 2010, ICEIS.

An Empirical Study of a Linear Regression Combiner on Multi-class Data Sets

Chun-Xia Zhang, Robert P. W. Duin, R. Duin, 2009, MCS.

Comparison Between Product and Mean Classi er Combination Rules

Robert P. W. Duin, David M. J. Tax, Martijn van Breukelen, 2009 .

Regularisation of Linear Classifiers by Adding Redundant Features

Robert P. W. Duin, Marina Skurichina, 2014, Pattern Analysis & Applications.

Classifiers for dissimilarity-based pattern recognition

Robert P. W. Duin, Elzbieta Pekalska, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

A non-iterative method for training feedforward networks

Robert P. W. Duin, M. A. Kraaijveld, W. F. Schmidt, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

On Combining One-Class Classifiers for Image Database Retrieval

Robert P. W. Duin, Pavel Paclík, Elzbieta Pekalska, 2002, Multiple Classifier Systems.

An Empirical Comparison of Kernel-Based and Dissimilarity-Based Feature Spaces

Robert P. W. Duin, Sang-Woon Kim, R. Duin, 2010, SSPR/SPR.

The Dipping Phenomenon

Robert P. W. Duin, Marco Loog, R. Duin, 2012, SSPR/SPR.

On Using Asymmetry Information for Classification in Extended Dissimilarity Spaces

Robert P. W. Duin, Mauricio Orozco-Alzate, Edel B. García Reyes, 2012, CIARP.

Supervised segmentation of textures in backscatter images

Geert M. P. van Kempen, Robert P. W. Duin, Pavel Paclík, 2002, Object recognition supported by user interaction for service robots.

Learning Curves for the Analysis of Multiple Instance Classifiers

Robert P. W. Duin, David M. J. Tax, D. Tax, 2008, SSPR/SPR.

Selective sampling based on the variation in label assignments

Robert P. W. Duin, Piotr Juszczak, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Group-Induced Vector Spaces

Robert P. W. Duin, Manuele Bicego, Elzbieta Pekalska, 2007, MCS.

On Feature Selection with Measurement Cost and Grouped Features

Geert M. P. van Kempen, Robert P. W. Duin, Pavel Paclík, 2002, SSPR/SPR.

A Study On Combining Image Representations For Image Classification And Retrieval

Robert P. W. Duin, Pavel Paclík, Elzbieta Pekalska, 2004, Int. J. Pattern Recognit. Artif. Intell..

Zero-error dissimilarity based classifiers pdf

Robert P. W. Duin, Elzbieta Pekalska, 2016, ArXiv.

Bagging and the Random Subspace Method for Redundant Feature Spaces

Robert P. W. Duin, Marina Skurichina, R. Duin, 2001, Multiple Classifier Systems.

A Discussion on the Classifier Projection Space for Classifier Combining

Robert P. W. Duin, Elzbieta Pekalska, Marina Skurichina, 2002, Multiple Classifier Systems.

Clustering-Based Construction of Hidden Markov Models for Generative Kernels

Robert P. W. Duin, Manuele Bicego, Vittorio Murino, 2009, EMMCVPR.

Nonlinear image processing using artificial neural networks

Robert P. W. Duin, Michael Egmont-Petersen, Piet W. Verbeek, 2003 .

Implementation and Use of Software Scanning on a Small CLIP4 Processor Array

Robert P. W. Duin, Johannes Buurman, 1988, Pattern Recognition.

A Generalized Kernel Approach to Dissimilarity-based Classification

Robert P. W. Duin, Pavel Paclík, Elzbieta Pekalska, 2002, J. Mach. Learn. Res..

Dimensionality Reduction of Hyperspectral Data via Spectral Feature Extraction

Robert P. W. Duin, Hamid Abrishami Moghaddam, Barat Mojaradi, 2009, IEEE Transactions on Geoscience and Remote Sensing.

The role of subclasses in machine diagnostics

Robert P. W. Duin, Alexander Ypma, Marina Skurichina, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Selection/Extraction of Spectral Regions for Autofluorescence Spectra Measured in the Oral Cavity

Robert P. W. Duin, Pavel Paclík, Henricus J. C. M. Sterenborg, 2004, SSPR/SPR.

Lauge Sørensen, Robert P. W. Duin, Marleen de Bruijne, 2010, MICCAI.

PRTools - Version 3.0 - A Matlab Toolbox for Pattern Recognition

Robert P. W. Duin, R. Duin, 2000 .

On the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions

Robert P. W. Duin, R. Duin, 1976, IEEE Transactions on Computers.

Robert P. W. Duin, José Salvador Sánchez, Mónica Millán-Giraldo, 2010, 2010 2nd International Workshop on Cognitive Information Processing.

The Applicability of Neural Networks to Non-linear Image Processing

Robert P. W. Duin, Piet W. Verbeek, Dick de Ridder, 1999, Pattern Analysis & Applications.

Towards Scalable Prototype Selection by Genetic Algorithms with Fast Criteria

Robert P. W. Duin, Heydi Mendez Vazquez, Mauricio Orozco-Alzate, 2014, S+SSPR.

Unsupervised Parameter Estimation of Non Linear Scaling for Improved Classification in the Dissimilarity Space

Robert P. W. Duin, Manuele Bicego, Mauricio Orozco-Alzate, 2016, S+SSPR.

The interaction between classification and reject performance for distance-based reject-option classifiers

Robert P. W. Duin, Pavel Paclík, David M. J. Tax, 2006, Pattern Recognit. Lett..

Appendix A: Topics Selected from Functional Analysis

Robert P. W. Duin, David M. J. Tax, F. van der Heijden, 2005 .

Prototype selection for dissimilarity-based classifiers

Robert P. W. Duin, Pavel Paclík, Elzbieta Pekalska, 2006, Pattern Recognit..

The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples

Robert P. W. Duin, Marco Loog, David M. J. Tax, 2013, MCS.

On Euclidean Corrections for Non-Euclidean Dissimilarities

Wan-Jui Lee, Horst Bunke, Robert P. W. Duin, 2008, SSPR/SPR.

The Role of Combining Rules in Bagging and Boosting

Robert P. W. Duin, Marina Skurichina, 2000, SSPR/SPR.

Spatial Representation of Dissimilarity Data via Lower-Complexity Linear and Nonlinear Mappings

Robert P. W. Duin, Elzbieta Pekalska, R. Duin, 2002, SSPR/SPR.

The characterization of classification problems by classifier disagreements

Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Training data selection for cancer detection in multispectral endoscopy images

Robert P. W. Duin, Marco Loog, Raimund Leitner, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

An Inexact Graph Comparison Approach in Joint Eigenspace

Wan-Jui Lee, Robert P. W. Duin, R. Duin, 2008, SSPR/SPR.

Feature Extraction and Selection

Robert P. W. Duin, David M. J. Tax, F. van der Heijden, 2005 .

Experiments with Classifier Combining Rules

Robert P. W. Duin, David M. J. Tax, D. Tax, 2000, Multiple Classifier Systems.

Hardware versus software implementations of fast image processing algorithms

Robert P. W. Duin, Pieter Jonker, F. C. A. Groen, 1988 .

Combining multi-scale dissimilarities for image classification

Robert P. W. Duin, Marco Loog, Yan Li, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).