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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.
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.
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)
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)
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.
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, 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.
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.
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., Van Meir, V., Tindemans, I., Leemans, A., and Van Der Linden, A., In Vivo Visualization of the Neuroanatomy and Brain Connectivity of Starling Brain Through Diffusion Tensor Imaging, in 6th Bi-Annual Meeting – Belgian Society for Neuroscience, Brussels, Belgium, 2005.
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 4th Annual Symposium – Young Belgian Magnetic Resonance Scientists, Brussels, Belgium, 2005.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., DTI parameters: Fractional Anisotropy, Radial and Axial Diffusivity reveal seasonal neuroplasticity in the adult songbird brain, in 4th annual meeting of the Society of Molecular Imaging, Keulen, Germany, 2005.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., Seasonal changes in neuronal connectivity in the songbird brain discerned by repeated in vivo DTI, in 13th Scientific Meeting - International Society for Magnetic Resonance in Medicine, Miami, USA, 2005, p. 715.
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.
G. De Groof, Verhoye, M., Leemans, A., and Van Der Linden, A., Using diffusion tensor imaging (DTI) to assess the neuronal plasticity and neuroconnectivity in the brain of a songbird, in Molecular & Cellular Basis of Neuroconnectivity, Leuven, Belgium, 2006.

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