F
Ferdinand van der Heijden
Researcher at University of Twente
Publications - 54
Citations - 3060
Ferdinand van der Heijden is an academic researcher from University of Twente. The author has contributed to research in topics: Geometric hashing & Estimator. The author has an hindex of 14, co-authored 54 publications receiving 2606 citations. Previous affiliations of Ferdinand van der Heijden include Netherlands Cancer Institute.
Papers
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Journal ArticleDOI
Efficient adaptive density estimation per image pixel for the task of background subtraction
TL;DR: This work presents recursive equations that are used to constantly update the parameters of a Gaussian mixture model and to simultaneously select the appropriate number of components for each pixel and presents a simple non-parametric adaptive density estimation method.
Journal ArticleDOI
Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.
Geert Litjens,Robert Toth,Wendy J. M. van de Ven,Caroline M. A. Hoeks,Sjoerd Kerkstra,Bram van Ginneken,G.R. Vincent,Gwenael Guillard,Neil Birbeck,Jindang Zhang,Robin Strand,Filip Malmberg,Yangming Ou,Christos Davatzikos,Matthias Kirschner,Florian Jung,Jing Yuan,Wu Qiu,Qinquan Gao,Philip J. Edwards,Bianca Maan,Ferdinand van der Heijden,Soumya Ghose,Soumya Ghose,Jhimli Mitra,Jhimli Mitra,Jason Dowling,Dean C. Barratt,Henkjan J. Huisman,Anant Madabhushi +29 more
TL;DR: Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, it is shown that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained.
Book
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB
TL;DR: In this paper, the authors present a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MatLab, which covers both the topics of pattern classification and optimal (state) estimation.
Book
Image Based Measurement Systems: Object Recognition and Parameter Estimation
TL;DR: The author has devoted a lot of thought to the measurement factor of image processing, of direct practical use in numerous sectors from industrial quality and robotics to medicine and biology.
BookDOI
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB, 2nd Edition
Dick de Ridder,David M. J. Tax,Lei Bangjun,Guangzhu Xu,Ming Feng,Yaobin Zou,Ferdinand van der Heijden +6 more
TL;DR: Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision.