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B. Koirala and Scheunders, P., “A Robust Supervised Method to Estimate Chlorophyll Ab Content from Spectral Reflectance”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 326-329.PDF icon igarss_2022.pdf (238.85 KB)
B. Koirala, Rasti, B., Bnoulkacem, Z., and Scheunders, P., “Nonlinear Spectral Unmixing Using Bézier Surfaces”, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, 2024.PDF icon nonlinear_spectral_unmixing_using_bezier_surfaces.pdf (9.66 MB)
B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Lorenz, S., Fuchs, M., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., “A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures”, IEEE Sensors Journal, 2023.PDF icon a_multisensor_hyperspectral_benchmark_dataset_for_unmixing_of_intimate_mixtures_1_.pdf (22.13 MB)
H. Khan, Giraldo, D., Beirinckx, Q., Sijbers, J., Lambin, P., Woodruff, H. C., and Peeters, L. M., “Exploring the Correlation between Disability Status and Brain Volumetric Measurements Using Real-World Retrospective Magnetic Resonance Images in People with Multiple Sclerosis”, Proceedings of the 9th Joint European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) - Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS) Meeting. October 11-13, Milan, Italy, 2023.
W. Keustermans, Huysmans, T., Danckaers, F., Zarowski, A., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “Investigating the relationship between shape and flow in the human nose using a statistical shape model”, 6th European Conference on Computational Mechanics (ECCM 6) - 7th European Conference on Computational Fluid Dynamics (ECFD 7), 11 – 15 June 2018, Glasgow, UK. 2018.PDF icon Download abstract (90.58 KB)
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model”, Computers in Biology and Medicine, vol. 117, no. 103600, pp. 1-13, 2020.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling”, Computers in Biology and Medicine, vol. 105, pp. 27-38, 2019.
W. Keustermans, Huysmans, T., Danckaers, F., Zarowski, A., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “High quality statistical shape modelling of the human nasal cavity and applications”, Royal Society Open Science, vol. 5, no. 12, 2018.PDF icon Download paper (1.85 MB)
J. Kenney, McInerney, S., McPhilemy, G., Najt, P., Scanlon, C., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Donohoe, G., Hallahan, B., McDonald, C., and Cannon, D., “P. 3.033 Lateralisation of the arcuate fasciculus in psychosis & the role in verbal learning & auditory verbal hallucinations”, European Neuropsychopharmacology, vol. 26, no. 1, pp. S76–S77, 2016.
J. P. M. Kenney, McPhilemy, G., Scanlon, C., Najt, P., McInerney, S., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Hallahan, B., McDonald, C., and Cannon, D. M., “The arcuate fasciculus network and verbal deficits in psychosis”, Translational Neuroscience, vol. 8, no. 1, pp. 117-126, 2017.
J. Kenney, McInerney, S., McPhilemy, G., Najt, P., Scanlon, C., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Donohoe, G., Hallahan, B., McDonald, C., and Cannon, D., “Lateralisation of the arcuate fasciculus in psychosis & the role in verbal learning & auditory verbal hallucinations”, vol. 26. Elsevier Science Bv, Po Box 211, 1000 Ae Amsterdam, Netherlands, pp. S76–S77, 2016.
P. Kempeneers, De Backer, S., Debruyn, W., and Scheunders, P., “Generic Wavelet-Based Hyperspectral Classification Applied to Vegetation Stress Detection”, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, pp. 610-614, 2005.
P. Kempeneers, De Backer, S., Debruyn, W., Provoost, S., and Scheunders, P., “Hyperspectral classification applied to the Belgian coastline”, in SPIE Remote Sensing, Bruges, Belgium, 19-22 september, 2005, vol. 5982.
P. Kempeneers, De Backer, S., Debruyn, W., and Scheunders, P., “Wavelet Based Feature Extraction for Hyperspectral Vegetation Monitoring”, in SPIE International Symposium on Remote Sensing, Image and Signal Processing for Remote Sensing IX, Barcelona, Spain, 2003, pp. 297-305.
P. Kempeneers, Sterckx, S., Debruyn, W., Park, Y., Ruddick, K., De Backer, S., and Scheunders, P., “Retrieval of oceanic constituents from ocean color using simulated annealing”, in IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, 25-29 July, 2005, vol. 8, pp. 5651-5654.
P. Kempeneers, De Backer, S., Delalieux, S., Sterckx, S., Debruyn, W., Coppin, P., and Scheunders, P., “Upscaling of spectroradiometer data for stress detection in orchards with remote sensing”, in SPIE Remote Sensing, Gran Canaria, 13-16 september, Maspalomas, Spain, 2004, vol. 127, pp. 37-45.
P. Kempeneers, “Information Extraction from Hyperspectral Images Applied to Vegetation”, 2007.
P. Kempeneers, De Backer, S., Deronde, B., Bertels, L., Debruyn, W., and Scheunders, P., “Classifying hyperspectral airborne imagery for vegetation survey along coastlines”, in IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Anchorage, USA, 20-24 september, Anchorage, USA, 2004, vol. 2, pp. 1475-1478.
P. Kempeneers, De Backer, S., Zarco-Tejada, P. J., Delalieux, S., Sepulcre-Cantó, G., Morales, F., Sagardoy, R., van Aardt, J., Coppin, P., and Scheunders, P., “Chlorophyll retrieval from canopy reflectance over orchards using hyperspectral techniques”, in 2nd International Symposium on Recent Advances in Quantitative Remote Sensing, 25-29 September 2006, Torrent (Valencia), Spain, 2006.
P. Kempeneers, Zarco-Tejada, P. J., North, P. R. J., De Backer, S., Delalieux, S., Sepulcre-Canto, G., Morales, F., van Aardt, J., Sagardoy, R., Coppin, P., and Scheunders, P., “Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery”, International Journal of Remote Sensing, vol. 29, pp. 5093-5111, 2008.
P. Kempeneers, De Backer, S., Tejada, Z. P. J., Delalieux, S., Canto, S. G., Iribas, M. F., van Aardt, J., Coppin, P., and Scheunders, P., “Stress detection in orchards with hyperspectral remote sensing data”, in SPIE Remote Sensing, Stockholm, Sweden, september 11-14, 2006, vol. 6359.
D. Gökbel Keklikoğlu, Francken, N., Huyge, B., Merdan, Z., De Beenhouwer, J., and Sijbers, J., “Dynamic flat field correction in edge illumination imaging”, in SPIE Developments in X-Ray Tomography XV, 2024, vol. 13152.
D. Kazantsev, Thompson, W. M., Lionheart, W. R. B., Van Eyndhoven, G., Kaestner, A. P., Dobson, K. J., Withers, P. J., and Lee, P. D., “4D-CT reconstruction with unified spatial-temporal patch-based regularization”, Inverse Problems and Imaging, vol. 9, no. 2, pp. 447-467, 2015.
D. Kazantsev, Van Eyndhoven, G., Lionheart, W. R. B., Withers, P. J., Dobson, K. J., McDonald, S. A., Atwood, R., and Lee, P. D., “Employing temporal self-similarity across the entire time domain in computed tomography reconstruction”, Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol. 373, 2015.
A. Karami, Beheshti, S., and M.Yazdi, “Hyperspectral Image Compression Using 3d Discrete Cosine Transform and Support Vector Machine Learning”, International Conference on Information Science, Signal Processing and their Applications . Montreal, Canada, 2012.

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