Publications

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Conference Paper
S. Yu, De Backer, S., and Scheunders, P., “Genetic Feature Selection Combined with Fuzzy K-NN for Hyperspectral Satellite Imagery”, in Intelligent Techniques and Soft Computing in Nuclear Science and Engineering, 2000, pp. 281-288.
S. Yu, De Backer, S., and Scheunders, P., “Genetic feature selection combined with fuzzy kNN for hyperspectral satellite imagery”, in Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International, 2000, pp. 702-704.
S. Yu, Scheunders, P., and De Backer, S., “Genetic Feature selection combined with composite fuzzy nearest neighbor classifers for high-dimensional remote sensing data”, in Proc. IEEE Intern. Conf. on Systems, Man & Cybernetics, October 8-11, Nashville,TN, 2000, pp. 1912-1916.
P. Scheunders, “A genetic approach towards optimal color image quantization”, in Proc. ICIP'96, IEEE Internat. Conference on Image Processing , III, Lausanne, september 16-19, 1996, pp. 1031-1034.
C. C. Hung, Coleman, T., and Scheunders, P., “The genetic algorithm approach and K-means clustering: their role in unsupervised training in image classification”, in Proc. IASTED International Conf. On Computer Graphics and Imaging , Halifax, Canada, june 1-3, 1998, pp. 103-106.
S. Yu and Scheunders, P., “Fuzzy markov chains approach to feature selection for high dimensional remote sensing data”, in Geoscience and Remote Sensing Symposium, 2001, pp. 3306-3308.
R. M. Soleimanzadeh, Karami, A., and Scheunders, P., “Fusion of hyperspectral and Lidar images using non-subsampled shearlet transform”, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.
V. Van Meir, Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., Sijbers, J., Verhoye, M., Balthazart, J., and Van Der Linden, A., “Functional Magnetic resonance Imaging meets animal vocal learner”, in Third One-Day Symposium of Young Belgian Magnetic Resonance Scientists, Brussels, Belgium, 2004.
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.
B. Koirala, Zahiri, Z., Khodadadzadeh, M., and Scheunders, P., “Fractional abundance estimation of mixed and compound materials by hyperspectral imaging.”, in 10th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), Sept 2019, Amsterdam, Netherlands, 2019, pp. pp. 1-5.PDF icon fractional_abundance_estimation_of_mixed_and_compound_materials_by_hyperspectral_imaging.pdf (742.67 KB)
S. Yu and Scheunders, P., “Feature selection for high-dimensional remote sensing data by a maximum entropy principal based optimization”, in Proc. Geoscience and Remote Sensing Symposium, 2001, pp. 3303-3305.
R. Heylen and Scheunders, P., “A fast geometric algorithm for solving the inversion problem in spectral unmixing”, in IEEE-WHISPERS 2012, Workshop on Hyperspectral Image and Signal Processing, Shanghai, June 4-7, 2012.
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.
B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., “An Extensive Multisensor Hyperspectral Benchmark Datasets of Intimate Mixtures of Mineral Powders”, in IEEE International Geoscience and Remote Sensing Symposium, 2023, pp. 5890-5893.PDF icon igarss_2022_1.pdf (1001.3 KB)
J. Ganseman, Mysore, G. J., Scheunders, P., and Abel, J. S., “Evaluation of a score-informed source separation system”, in Proc. 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, the Netherlands, August 2010, 2010, pp. 219-224.
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., “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.
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.
Z. Mahmood and Scheunders, P., “Enhanced visualization of hyperspectral images”, in Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, 2010, pp. 991 -994.
J. - P. Jacobs, Thoonen, G., Tuia, D., Camps-Valls, G., Haest, B., and Scheunders, P., “Domain adaptation with Hidden Markov Random Fields”, in Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International, Melbourne, VIC, Australia, 2013, pp. 3112-3115.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Wuyts, N., and Scheunders, P., “Detection of plant responses to drought using close-range hyperspectral imaging in a high-throughput phenotyping platform”, in IEEE Whispers 2018, Workshop on Hyperspectral Image and Signal Processing, Amsterdam, 23-26 September , 2018.
D. Meersman, Scheunders, P., and Van Dyck, D., “Detection of microcalcifications using non-linear filtering”, in Proc. EUSIPCO'98, European Signal Processing Conference, 1998, pp. 2465-2468.
D. Meersman, Scheunders, P., and Van Dyck, D., “Detection of microcalcifications using neural networks”, in Digital Mammography, 1996, pp. 287-290.
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.
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.

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