N. Zhang (Ning)

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

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. Article 2977. Advance online publication. https://doi.org/10.3390/rs14132977

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. Advance online publication. 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

Zhang, N., & Zhang, L. (2018). SSGD: Superpixels using the shortest gradient distance. In 2017 IEEE International Conference on Image Processing (ICIP) (pp. 3869-3873). IEEE. https://doi.org/10.1109/ICIP.2017.8297007