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Robert P. W. Duin
Researcher at Delft University of Technology
Publications - 301
Citations - 32657
Robert P. W. Duin is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Classifier (UML) & Random subspace method. The author has an hindex of 62, co-authored 301 publications receiving 31072 citations. Previous affiliations of Robert P. W. Duin include Utrecht University.
Papers
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Journal Article
Dissimilarity-based classification of seismic signals at nevado del ruiz volcano
TL;DR: In this paper, a Bayesian classifier constructed on dissimilarity representations is proposed for automatic classification of seismic signals, which is a feasible and reliable alternative to feature-based representations.
Proceedings ArticleDOI
Early diagnosis of dementia based on intersubject whole-brain dissimilarities
Stefan Klein,Marco Loog,F. van der Lijn,T. den Heijer,Alexander Hammers,M. de Bruijne,A. van der Lugt,Robert P. W. Duin,Monique M.B. Breteler,Wiro J. Niessen +9 more
TL;DR: The potential of whole-brain intersubject dissimilarities to aid in early diagnosis of dementia is demonstrated, using nonrigid registration of MR brain scans in combination with dissimilarity-based pattern recognition techniques.
Journal ArticleDOI
A study on combining image representations for image classification and retrieval
TL;DR: It is shown that combining of the SVDD descriptions improves the retrieval performance with respect to ranking, on the contrary to the Mahalanobis case.
Uncertainty sampling methods for one-class classifiers
Piotr Juszczak,Robert P. W. Duin +1 more
TL;DR: The goal of this paper is to show why the best or most often used selective sampling methods for two- or multi-class problems are not necessarily the best ones for the one-class classification problem.
Book ChapterDOI
The Science of Pattern Recognition. Achievements and Perspectives
TL;DR: The engineering approach to pattern recognition is an attempt to build systems that simulate this phenomenon and by doing that, scientific understanding is gained of what is needed in order to recognize patterns, in general.