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F. Danckaers, Huysmans, T., and Sijbers, J., Adaptable digital human models from 3D body scans, in DHM and Posturography, vol. VI, Academic Press, 2019, pp. 459-470.
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., Rogge, S., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Building a statistical shape model of the interior and exterior of the bell pepper, 30th Targeted Technologies for Sustainable Food Systems (EFFoST) International Conference, vol. 28-30 November. Vienna, Austria, 2016.
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, Huysmans, T., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Building 3D Statistical Shape Models of Horticultural Products, Food and Bioprocess Technology, vol. 10, no. 11, pp. 2100-2112, 2017.PDF icon Download paper (1.73 MB)
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.
F. Danckaers, Huysmans, T., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Building a Statistical Shape Model of the Apple from Corresponded Surfaces, Chemical Engineering Transactions, vol. 44, pp. 49-54, 2015.PDF icon Download paper (696.94 KB)
F. Danckaers, The Development of 3D Statistical Shape Models for Diverse Applications, 2019.
M. Das and Liang, Z., Approximated transport-of-intensity equation for coded-aperture x-ray phase-contrast imaging, Optics Letters, vol. 39, no. 18, p. 5395, 2014.
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 and Scheunders, P., Texture segmentation by frequency-sensitive elliptical competitive learning, Image and Vision Computing, vol. 19, pp. 639-648, 2001.
S. De Backer, Pizurica, A., Huysmans, B., Philips, W., and Scheunders, P., Denoising of Multicomponent Images Using Wavelet Least-Squares Estimators, Image and Vision Computing, vol. 26, pp. 1038-1051, 2008.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Five - Optimal experiment design for nanoparticle atom counting from ADF STEM images, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
S. De Backer, Cornelissen, F., Lemeire, J., Nuydens, R., Meert, T., Schelkens, P., and Scheunders, P., Mosiacing of Fibered Fluorescence Microscopy Video, Lecture notes in Computer Science, vol. 5259, pp. 915-923, 2008.
S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., A Band Selection Technique for Spectral Classification, IEEE Geoscience and Remote Sensing Letters, vol. 2, pp. 319-323, 2005.
S. De Backer, Unsupervised Pattern Recognition - Dimensionality Reduction and Classification, University of Antwerp, Antwerp, 2002.
S. De Backer and Scheunders, P., A competitive elliptical clustering algorithm, Pattern Recognition Letters, vol. 20, pp. 1141-1147, 1999.
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.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Two - Statistical parameter estimation theory: principles and simulation studies, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
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.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Three - Efficient fitting algorithm, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Four - Atom counting, in Advances in Imaging and Electron Physics,, vol. 217, Science Direct Elsevier, 2021.
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.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Eight - General conclusions and future perspectives, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
S. De Backer, Naud, A., and Scheunders, P., Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction, Pattern Recognition Letters, vol. 19, pp. 711-720, 1998.

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