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2022
P. Ghosh, Roy, S. Kumar, Koirala, B., Rasti, B., and Scheunders, P., Hyperspectral Unmixing Using Transformer Network, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.PDF icon transformer_unmixing.pdf (6.32 MB)
T. De Kerf, Pipintakos, G., Zahiri, Z., Vanlanduit, S., and Scheunders, P., Identification of corrosion minerals usning shortwave infrared hyperspectral imaging, Sensors, vol. 22, no. 1, p. 407, 2022.PDF icon sensors-22-00407-v2.pdf (4.41 MB)
V. Anania, Collier, Q., Veraart, J., Buikema, A. Eline, Vanhevel, F., Billiet, T., Jeurissen, B., den Dekker, A. J., and Sijbers, J., Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model, NeuroImage, vol. 256, p. 119219, 2022.
T. Van De Looverbosch, Jiaqi, H., Tempelaere, A., Kelchtermans, K., Verboven, P., Tuytelaars, T., Sijbers, J., and Nicolai, B., Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images, Computers and Electronics in Agriculture, vol. 197, no. 106962, pp. 1-14, 2022.
D. Giraldo, Smith, R. E., Struyfs, H., Niemantsverdriet, E., De Roeck, E., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., and Jeurissen, B., Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022.
D. Giraldo, Smith, R. E., Struyfs, H., Niemantsverdriet, E., De Roeck, E., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., and Jeurissen, B., Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022.
D. Giraldo, Smith, R. E., Struyfs, H., Niemantsverdriet, E., De Roeck, E., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., and Jeurissen, B., Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022.
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, no. 5522815, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.57 MB)
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.52 MB)
Q. Beirinckx, Jeurissen, B., Nicastro, M., Poot, D. H. J., Verhoye, M., den Dekker, A. J., and Sijbers, J., Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping, Computerized Medical Imaging and Graphics, vol. 100, no. 102071, pp. 1-16, 2022.PDF icon Download paper (15.42 MB)PDF icon Download supplementary material (1.35 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Gloaguen, R., and Scheunders, P., MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6518-6530, 2022.PDF icon ms2a-net_multiscale_spectralspatial_association_network_for_hyperspectral_image_clustering.pdf (12.33 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Gloaguen, R., and Scheunders, P., MS2A-Net: multi-view spectral-spatial association network for hyperspectral image clustering, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 6518-6530, 2022.PDF icon ms2a-net_multiscale_spectralspatial_association_network_for_hyperspectral_image_clustering.pdf (12.33 MB)
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Bikram, K., and Scheunders, P., Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress, Computers and Electronics in Agriculture, vol. 195, p. 106806, 2022.PDF icon non-destructive_analysis_of_plant_physiological_traits_using_hyperspectral.pdf (5.53 MB)
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Koirala, B., and Scheunders, P., Non-Destructive Analysis of Plant Physiological Traits Using Hyperspectral Imaging: A Case Study on Drought Stress, Computers and Electronics in Agriculture, vol. 195, no. 106806, 2022.PDF icon 1-s2.0-s0168169922001235-main.pdf (5.53 MB)
M. Yosifov, Reiter, M., Heupl, S., Gusenbauer, C., Fröhler, B., R. Gutierrez, F. -, De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Probability of Detection applied to X-ray inspection using numerical simulations, Nondestructive Testing and Evaluation, vol. 37, no. 5, pp. 536-551, 2022.
T. De Kerf, Gestels, A., Janssens, K., Steenackers, G., Scheunders, P., and Vanlanduit, S., Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging, RSC Advances, vol. 12, pp. 32775-32783, 2022.
T. De Kerf, Gestels, A., Janssens, K., Steenackers, G., Scheunders, P., and Vanlanduit, S., Quantitative detection of corrosion minerals in carbon steel using shortwave infrared hyperspectral imaging, RSC Advances, vol. 12, pp. 32775-32783, 2022.
B. Koirala, Zahiri, Z., and Scheunders, P., A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance, IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1-13, 2022.PDF icon soil_moisture_content.pdf (7.95 MB)
G. Zhang, Scheunders, P., Cerra, D., and Muller, R., Shadow-aware nonlinear spectral unmixing for hyperspectral imagery, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 5514-5533, 2022.PDF icon shadow-aware_nonlinear_spectral_unmixing_for_hyperspectral_imagery.pdf (9.51 MB)
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging, Frontiers in Neuroscience, pp. 1-18, 2022.PDF icon Download paper (5.96 MB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging, Frontiers in Neuroscience, pp. 1-18, 2022.PDF icon Download paper (5.96 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 15, pp. 284-296, 2022.PDF icon mdc_jstars-final_version.pdf (6.53 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Scheunders, P., and Gloaguen, R., Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , vol. 15, pp. 284-296, 2022.PDF icon mdc_jstars-final_version.pdf (6.53 MB)

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