prof.dr. N. Kerle (Norman)

Engineering & Materials Science

# Damage Detection
# Disasters
# Landslides
# Remote Sensing

Earth & Environmental Sciences

# Damage
# Detection
# Disaster
# Landslide

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Applied Earth Sciences (AES)

Zhang, N. , Nex, F. C. , Vosselman, G. , & Kerle, N. (2023). Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation. In CVPR 2023 (pp. 18537-18546) https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Lite-Mono_A_Lightweight_CNN_and_Transformer_Architecture_for_Self-Supervised_Monocular_CVPR_2023_paper.html

Sedhain, S., van den Homberg, M., Teklesadik, A. , van Aalst, M. K. , & Kerle, N. (2023). Evaluating the explainability and performance of an elementary versus a statistical impact-based forecasting model. Abstract from EGU General Assembly 2023, Vienna, Austria. https://doi.org/10.5194/egusphere-egu23-11434

Karam, S. , Nex, F., Chidura, B. T. , & Kerle, N. (2022). Microdrone-Based Indoor Mapping with Graph SLAM. Drones, 6(11), 1-26. [352]. https://doi.org/10.3390/drones6110352

Tilon, S. , Nex, F. , Vosselman, G., Llave, I. S. D. L. , & Kerle, N. (2022). Towards improved unmanned aerial vehicle edge intelligence: a road infrastructure monitoring case study. Remote sensing, 14(16), [4008]. https://doi.org/10.3390/rs14164008

Zhang, N. , Nex, F. C. , Vosselman, G. , & Kerle, N. (2022). Training a disaster victim detection network for UAV search and rescue using harmonious composite images. Remote sensing, 14(13), 1-19. [2977]. https://doi.org/10.3390/rs14132977

Karam, S. , Nex, F. C., Karlsson, O., Rydell, J., Bilock, E., Tulldahl, M. , Kerle, N., & Holmberg, M. (2022). Micro and macro quadcopter drones for indoor mapping to support disaster management. In S. Hinz, R. Q. Feitosa, M. Weinmann, & B. Jutzi (Eds.), ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Vol. Volume V-1-2022, pp. 203-210). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). Copernicus. https://doi.org/10.5194/isprs-annals-v-1-2022-203-2022

Zhang, N. , Nex, F. C. , Vosselman, G. , & Kerle, N. (2022). Unsupervised harmonious image composition for disaster victim detection. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences: Congress “Imaging today, foreseeing tomorrow”, Commission III (B3-2022 ed., Vol. 43, pp. 1189–1196). (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information ). Copernicus. https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1189-2022

Zhang, N. , Nex, F. C. , Kerle, N. , & Vosselman, G. (2022). LISU: Low-light indoor scene understanding with joint learning of reflectance restoration. ISPRS journal of photogrammetry and remote sensing, 183, 470-481. https://doi.org/10.1016/j.isprsjprs.2021.11.010

Zhang, N. , Nex, F. C. , Kerle, N. , & Vosselman, G. (2021). Towards Learning Low-Light Indoor Semantic Segmentation with Illumination-Invariant Features. In N. Paparoditis, C. Mallet, F. Lafarge, M. Y. Yang, A. Yilmaz, J. D. Wegner, F. Remondino, T. Fuse, & I. Toschi (Eds.), The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (B2-2021 ed., Vol. XLIII-B2-2021, pp. 427-432). International Society for Photogrammetry and Remote Sensing (ISPRS). https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-427-2021

Ghaffarian, S. , Roy, D. , Filatova, T. , & Kerle, N. (2021). Agent-based modelling of post-disaster recovery with remote sensing data. International journal of disaster risk reduction, 60, 1-15. [102285]. https://doi.org/10.1016/j.ijdrr.2021.102285

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Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.