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P. Scheunders, Tuia, D., and Moser, G., “Contributions of Machine Learning to Remote Sensing Data Analysis”, in Comprehensive Remote Sensing, vol. 2, 2018, pp. 199-243.
P. Scheunders, “A wavelet representation of multispectral images; in: Frontiers of Remote Sensing Information Processing”, C. H. Chen, Ed. World Scientific, 2003, pp. 197-224.
P. Scheunders, “Genetic optimal quantization of gray-level and color images”, in Proceedings ACCV'95, Second Asian Conference on Computer Vision, Singapore, 5-8 december, 1995, pp. 94-98.
P. Scheunders, “Joint quantization and error-diffusion of color images using competitive learning”, Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, pp. 137-140, 1998.
P. Scheunders, “Wavelet representations of multivalued images”, in Wavelet Applications in Industrial Processing, part of the International Symposium on Photonics Technologies for Robotics, Automation, and Manufacturing , 27-31 October 2003, Providence, RI USA, 2003, pp. 203-215.
P. Scheunders and De Backer, S., “Multispectral image fusion and merging using multiscale fundamental forms”, in Proc. ICIP01, IEEE International Conference on Image Processing, Thessaloniki, Greece, 2001, pp. 902-905.
P. Scheunders, “An orthogonal wavelet representation of multivalued images”, IEEE Transactions on Image Processing, vol. 12, pp. 718-725, 2003.
P. Scheunders, “A genetic c-means clustering algorithm applied to color image quantization”, Pattern Recognition, vol. 30, pp. 859-866, 1997.
P. Scheunders and De Backer, S., “Fusion and merging of multispectral images using multiscale fundamental forms”, Journal of the Optical Society of America A, vol. 18, pp. 2468-2477, 2001.
P. Scheunders, “Denoising of multispectral images using wavelet thresholding”, in Proc. SPIE conference on Image and Signal Processing for Remote Sensing IX, part of the International Symposium on Remote Sensing, Barcelona, Spain, 2003, pp. 28-35.
P. Scheunders, De Backer, S., Pizurica, A., Huysmans, B., and Philips, W., “Bayesian Wavelet-based Denoising of Multicomponent Images”, in Proceedings Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, 9-12 september, Vol. 6763-OK (12 pages), 2007.
P. Scheunders, “Multivalued image segmentation based on first fundamental form”, in Proc. ICIAP, International Conference on Image Analysis and Processing, Palermo, Italy, 2001, pp. 185-190.
P. Scheunders, “A multivalued image wavelet representation based on multiscale fundamental forms”, IEEE Transactions on Image Processing, vol. 11, pp. 568-575, 2002.
P. Scheunders, “Wavelet-based enhancement and denoising using multiscale structure tensor”, in Proceedings of the IEEE International Conference on Image Processing, Rochester NY, 2002, pp. 569-572.
P. Scheunders and De Backer, S., “Wavelet denoising of multicomponent images, using Gaussian Scale Mixture models and a noise-free image as priors”, IEEE Transactions on Image Processing, vol. 16, pp. 1865-1872, 2007.
P. Scheunders, “Bayesian techniques for multi/hyperspectral image processing”, in 4th IEEE Conference on Industrial Electronics and Applications, Xi’an, China, May 25-27, 2009, pp. 1-10.
P. Scheunders, Van Hove, H., and Livens, S., “On the local optimality of image quantizers”, in Proc. ICPR'96 IEEE Internat. Conference on Pattern Recognition,, D, pp. 664-668, Vienna, august 25-30, 1996, pp. 664-668.
P. Scheunders, “Multispectral image fusion using local mapping techniques”, in Proc. ICPR2000, International Conference on Pattern Recognition, Barcelona, Spain, september 3-7, 2000, pp. 311-314.
P. Scheunders, Livens, S., Van de Wouwer, G., Vautrot, P., and Van Dyck, D., “Wavelet-based texture analysis”, Intern. Journal on Computer Science and Information Management, vol. 1, pp. 22-34, 1998.
P. Scheunders, “Wavelet thresholding of multispectral images”, in Proc. ACIVS03, Andvanced Concepts for intelligent vision systems , Ghent, 2003, pp. 255-259.
P. Scheunders, “Wavelet thresholding of multivalued images”, IEEE Transactions on Image Processing, vol. 13, pp. 475-483, 2004.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., and Sijbers, J., “Moving Statistical Body Shape Models Using Blender”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 28–38.
S. Scataglini, Danckaers, F., Huysmans, T., Sijbers, J., and Andreoni, G., “Design smart clothing using digital human models”, in DHM and Posturography, Academic Press, 2019, pp. 683-698.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., Sijbers, J., and Andreoni, G., “Using 3D Statistical Shape Models for Designing Smart Clothing”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 18–27.
J. Sanctorum, Van Wassenbergh, S., Nguyen, V., De Beenhouwer, J., Sijbers, J., and Dirckx, J. J. J., “Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique”, Physics in Medicine and Biology, vol. 66, no. 16, 2021.PDF icon Download paper (4.28 MB)

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