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D. Ali Chaghdo, Koirala, B., Fontaine, L., De Kock, T., Hayen, R., and Scheunders, P., “Moisture Content Estimation of Heterogenous Porous Stones Using Hyperspectral Imaging”, in 2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2025, pp. 1-5.PDF icon danish_whispers_2025.pdf (678.02 KB)
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W. D'haes, “A highly optimized nonlinear least squares technique for sinusoidal analysis: From O(K^2N) to O(N log(N))”, in Proceedings of the 116th Audio Engineering Society Convention (AES), Berlin, Germany, 2004.
W. D'haes, “A highly optimized method for computing amplitudes over a windowed short time signal: From O(K^2N) to O(N log(N))”, in Proceedings of the IEEE Benelux Signal Processing Symposium, Hilvarenbeek, the Netherlands, 2004.
W. D'haes and Rodet, X., “Discrete Cepstrum Coefficients as Perceptual Features”, in International Computer Music Conference (ICMC), 2003.
W. D'haes and Rodet, X., “A New Estimation Technique for Determining the Control Parameters of a physical model of a trumpet”, in 6th International Conference on Digital Audio Effects (DAFx03), London, England, 2003.
W. D'haes, Van Dyck, D., and Rodet, X., “Control Parameter Estimation for a Physical Model of a Trumpet Using Pattern Recognition”, in IEEE Workshop on Model Based Processing and Coding of Audio (MPCA), Leuven, Belgium, 2002.
W. D'haes and Rodet, X., “Physical Constraints for the Control of a Physical Model of a Trumpet”, in International Conference on Digital Audio Effects (DAFx), Hamburg, Germany, 2002.
W. D'haes, Van Dyck, D., and Rodet, X., “An efficient branch and bound seach algorithm for computing K nearest neighbors in a multidimensional vector space”, in IEEE Advanced Concepts for Intelligent Vision Systems (ACIVS), Gent, Belgium, 2002.
W. D'haes, Van Dyck, D., and Rodet, X., “An efficient branch and bound seach algorithm for computing K nearest neighbors in a multidimensional vector space”, in Signal Processing, Pattern Recognition and Applications (SPPRA), Crete, Greece, 2002.
W. D'haes and Rodet, X., “Automatic Estimation of Control Parameters: An Instance-Based Learning Approach”, in International Computer Music Conference (ICMC), Havana, Cuba, 2001.
A. Dabravolski, Batenburg, K. J., and Sijbers, J., “Adaptive Zooming in X-ray Computed Tomography”, in 1st International Conference on Tomography of Materials and Structures (ICTMS), Ghent, Belgium, 2013, pp. 5-8.PDF icon Download full paper (633.7 KB)PDF icon Download poster (1.18 MB)
A. Dabravolski, Batenburg, K. J., and Sijbers, J., “Dynamic Angle Selection in X-ray Computed Tomography”, in 1st International Conference on Tomography of Materials and Structures (ICTMS), Ghent, Belgium, 2013, pp. 27-30.PDF icon Download full paper (447.03 KB)PDF icon Download presentation (682.25 KB)
A. Dabravolski, De Beenhouwer, J., and Sijbers, J., “Projection-based polygon estimation in X-ray computed tomography”, in 6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS), 2016, pp. 41-50.PDF icon Download paper (615.72 KB)
F. Danckaers, Huysmans, T., Lacko, D., and Sijbers, J., “Evaluation of 3D Body Shape Predictions Based on Features”, in 6th International Conference on 3D Body Scanning Technologies, Lugano, Switserland, 2015, pp. 258-265.PDF icon 27danckaers.pdf (2.55 MB)
F. Danckaers, Huysmans, T., Lacko, D., Ledda, A., Verwulgen, S., Van Dongen, S., and Sijbers, J., “Correspondence Preserving Elastic Surface Registration with Shape Model Prior”, in International Conference of Pattern Recognition, 2014, vol. 22, pp. 2143-2148.PDF icon paper (550.57 KB)
F. Danckaers, Van Houtte, J., Booth, B. G., Verstreken, F., and Sijbers, J., “Statistical shape and pose model of the forearm for custom splint design”, in IEEE International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1669-1672.PDF icon Download paper (1.54 MB)
F. Danckaers, Huysmans, T., Hallemans, A., De Bruyne, G., Truijen, S., and Sijbers, J., “Full Body Statistical Shape Modeling with Posture Normalization”, in The 8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017), Los Angeles, California, USA, 2018, vol. 591, pp. 437-448.PDF icon Download paper (1.12 MB)
F. Danckaers, Lacko, D., Verwulgen, S., De Bruyne, G., Huysmans, T., and Sijbers, J., “A Combined Statistical Shape Model of the Scalp and Skull of the Human Head”, in 8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017), Los Angeles, California, USA, 2018, vol. 591, pp. 538-548.PDF icon Download paper (934.68 KB)
F. Danckaers, Scataglini, S., Haelterman, R., Van Tiggelen, D., Huysmans, T., and Sijbers, J., “Automatic Generation of Statistical Shape Models in Motion”, in Advances in Human Factors in Simulation and Modeling (AHFE 2018), Cham, 2019, vol. 780, pp. 170–178.
S. De Backer and Scheunders, P., “Texture segmentation by frequency-sensitive elliptical competitive learning”, in Proc. ICIAP99, International Conference on Image Analysis and Processing , Venice, Italy, september 27-29, 1999, pp. 64-69.
S. De Backer and Scheunders, P., “Enhancement of fMRI image series with the aid of an anatomical image”, in ISBI’06, IEEE International Symposium on Biomedical Imaging, Arlington, Virginia, april 6-9, 2006, pp. 1052-1055.
S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., “Classification of Dune Vegetation from Remotely Sensed Hyperspectral Images”, in Image Analysis and Recognition Proc. of International Conference on Image Analysis and Recognition, Porto, Portugal, 2004, pp. 497-503.
S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., “Wavelet Based Hyperspectral Data Analysis for Vegetation Stress Classification”, in Proc. of Advanced Concepts for Intelligent Vision Systems, Brussels, Belgium, 2004, pp. 387-391.
B. De Boeck, Scheunders, P., and Van Dyck, D., “From inductive inference to the fundamental equations of measuerement”, in Proc. First International Conference on Complex Systems, 2000, pp. 115-122.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., “Using diffusion tensor imaging (DTI) to assess the neuronal plasticity in the brain of a songbird”, in XXeme Congres du Groupement d'Etudes de Resonance Magnetique, Blankenberge, Belgium, 2006.

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