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R. Heylen, Akhter, M. A., and Scheunders, P., A fast alternative for the pixel purity index algorithm, in IEEE IGARSS 2015, International Geoscience and Remote Sensing Symposium, Milan, Italy, July 26-31, 2015, pp. 1781-1784.
R. Heylen, Parente, M., and Scheunders, P., Estimation of the intrinsic dimensionality in hyperspectral imagery via the hubness phenomenon, in LVA ICA 2017, International conference on latent variable analysis and signal separation, Grenoble, France, February 21-23, Lecture Notes in Computer Science, 2017, vol. 10169.
R. Heylen and Scheunders, P., Spectral unmixing using distance geometry, in IEEE-WHISPERS 2011, Workshop on Hperspectral Image and Signal Processing, Lisbon, Portugal, 6-9 June, 2011.
R. Heylen and Scheunders, P., Nonlinear unmixing with a multilinear mixing model, in IEEE Whispers 2015, Workshop on Hyperspectral Image and Signal Processing, June 2-5, Tokyo, 2015.
R. Heylen, Akhter, M. A., and Scheunders, P., Solving the Hyperspectral Unmixing Problem with Projection Onto Convex Sets, in 21st European Signal Processing Conference (EUSIPCO), September 2013, Marrakech, Morocco, 2013.
R. Heylen, Zare, A., Gader, P., and Scheunders, P., Hyperspectral unmixing with endmember variability via alternating angle minimization, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4983-4993, 2016.
R. Heylen, Burazerovic, D., and Scheunders, P., Nonlinear spectral unmixing by geodesic simplex volume maximization, IEEE Journal of Selected Topics in Signal Processing, vol. 5, pp. 534-542, 2011.
R. Heylen and Scheunders, P., Estimating the number of endmembers in hyperspectral imagery with nearest neighbor distances, in IEEE IGARSS2012, International Geoscience and Remote Sensing Symposium, Munich, July 22-27, 2012, pp. 1377-1380.
R. Heylen, Scheunders, P., and Gader, P., Handling spectral variability with alternating angle minimization, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
R. Heylen and Scheunders, P., Hyperspectral unmixing using an active set algorithm, in IEEE ICIP 2014, International Conference on Image Processing, October 27-30, Paris, France , 2014.
R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., Nonlinear hyperspectral unmixing with graphical models, IEEE Transaction on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4844-4856, 2019.PDF icon published.pdf (3.15 MB)
R. Heylen and Scheunders, P., A multilinear mixing model for nonlinear spectral unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 240-251, 2016.
R. Heylen, Burazerovic, D., and Scheunders, P., Fully constrained least-squares spectral unmixing by simplex projection, IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4112-4122, 2011.PDF icon PDF (1.11 MB)Package icon Matlab code (1.93 KB)
R. Heylen and Scheunders, P., Multi-dimensional Pixel Purity Index, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
M. Das and Liang, Z., SPIE ProceedingsSingle-step, quantitative x-ray differential phase contrast imaging using spectral detection in a coded aperture setup, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941252.
M. Das, Kandel, B., Park, C. Soo, and Liang, Z., SPIE ProceedingsEnergy calibration of photon counting detectors using x-ray tube potential as a reference for material decomposition applications, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941214.
S. Hosseinnejad, Bosch, E. G. T., Kohr, H., Lazić, I., Zharinov, V., Franken, E., Sijbers, J., and De Beenhouwer, J., 3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior, Microscopy Conference. 2021.PDF icon Download abstract (534.35 KB)
T. Hu, Li, W., Liu, N., Tao, R., Zhang, F., and Scheunders, P., Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1516-1533, 2021.PDF icon tgrs_2020.pdf (5.71 MB)
T. Hu, Liu, N., Li, W., Tao, R., Zhang, F., and Scheunders, P., Destriping Hyperspectral Imagery By Adaptive Anisotropic Total Variation And Truncated Nuclear Norm, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
K. Hufkens, Ceulemans, R., and Scheunders, P., Ecotones in vegetation ecology: methodology and definitions revisited, Ecological Research, vol. 24, pp. 977-986, 2009.
K. Hufkens, Scheunders, P., and Ceulemans, R., Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada, Ecological Informatics, vol. 4, pp. 1-7, 2009.
K. Hufkens, Ceulemans, R., and Scheunders, P., Estimating the ecotone width in patchy ecotones using a sigmoid wave approach, Ecological Informatics, vol. 3, pp. 97-104, 2008.
K. Hufkens, Thoonen, G., Vanden Borre, J., Scheunders, P., and Ceulemans, R., Habitat reporting of a heathland site: Classification probabilities as additional information, a case study, Ecological Informatics, vol. 5, pp. 248 - 255, 2010.
S. Huijs, Huysmans, T., De Jong, A., Arnout, N., Sijbers, J., and Bellemans, J., Principal component analysis as a tool for determining optimal tibial baseplate geometry in modern TKA design, Acta Orthop Belg, vol. 84, no. 4, pp. 452-460, 2018.
C. C. Hung, Scheunders, P., Pham, M., Su, M. C., and Coleman, T., Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification, International Journal of Fuzzy Systems, vol. 6, pp. 107-117, 2004.

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