Publications

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2019
V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields, Remote Sensing, vol. 11, 2019.PDF icon remotesensing-11-00624.pdf (1.5 MB)
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.
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)
B. Koirala and Scheunders, P., A semi-supervised method for Nonlinear Hyperspectral Unmixing, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Yokohama, Japan, 2019, 2019, pp. pp. 361-364.
V. Andrejchenko, Zahiri, Z., Heylen, R., and Scheunders, P., A spectral mixing model accounting for multiple reflections and shadow, in IGARSS 2019, International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 286-289.
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., A supervised method for nonlinear hyperspectral unmixing, Remote Sensing, vol. 11, no. 20 , 2019.PDF icon remotesensing-11-02458-v3.pdf (3.23 MB)
2018
J. Blanc-Talon, Helbert, D., Philips, W., Popescu, D., and Scheunders, P., ACIVS 2018, Advanced Concepts for Intelligent Vision Systems , Lecture Notes in Computer Science, vol. 11182. 2018.
Z. Zahiri, Ribbens, B., Vanlanduit, S., and Scheunders, P., Automatic Detection of Surface Damages on Steel Structures using Near Infrared Hyperspectral Imaging, 9th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS). 2018.
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform, ISPRS Journal of Photogrammetry and Remote Sensing , vol. 138, pp. 121-138, 2018.
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.
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.
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.
H. Rezaei, Karami, A., and Scheunders, P., Hyperspectral and multispectral image fusion based on spectral matching in the shearlet domain, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.
V. Andrejchenko, Heylen, R., Liao, W., Philips, W., and Scheunders, P., MRF-based decision fusion for hyperspectral image classification, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018.
B. Koirala, Heylen, R., and Scheunders, P., A NEURAL NETWORK METHOD FOR NONLINEAR HYPERSPECTRAL UNMIXING, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018, pp. pp. 4233-4236.
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., Noise reduction in hyperspectral imagery: overview and application, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
T. Dox, Heylen, R., and Scheunders, P., Spectral variability in a multilinear mixing model, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.
2017
J. Blanc-Talon, Penne, R., Philips, W., Popescu, D., and Scheunders, P., ACIVS 2017, Advanced Concepts for Intelligent Vision Systems, Lecture Notes in Computer Science, vol. 10617. 2017.
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, Parente, M., and Scheunders, P., Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017.
A. J. Rebelo, Scheunders, P., Esler, K. J., and Meire, P., Evaluating palmiet wetland decline: a comparison of three methods, Remote Sensing Applications: Society and Environment, vol. 8, pp. 212-223, 2017.
R. Luo, Liao, W., Zhang, H., Zhang, L., Pi, Y., Scheunders, P., and Philips, W., Fusion of Hyperspectral and LiDAR Data for Classification of Cloud-Shadow Mixed Remote Sensing Scene, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 8, pp. 3768-3781, 2017.
B. Haest, Vanden Borre, J., Spanhove, T., Thoonen, G., Delalieux, S., Kooistra, L., Mücher, C. A., Paelinckx, D., Scheunders, P., and Kempeneers, P., Habitat mapping and quality assessment of NATURA 2000 Heatland using airborne imaging spectroscopy, Remote Sensing, vol. 9, no. 3, 2017.
M. Brackx, Van Wittenberghe, S., Verhelst, J., Scheunders, P., and Samson, R., Hyperspectral leaf reflectance of Carpines betulus L. saplings for urban air quality estimation, Environmental Pollution, vol. 220, pp. 159-167, 2017.

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