Communications publiées lors de congrès ou colloques nationaux et internationaux (15)
  1. 1. Govoorts, J., Grippa, T., Vanhuysse, S., & Wolff, E. (2023). Mapping urban deprivation from Sentinel 1/2 using artificial intelligence and weakly labelled data. 2023 Joint Urban Remote Sensing Event (JURSE) 2023 Joint Urban Remote Sensing Event (JURSE)(2023: Heraklon, Greece) doi:10.1109/JURSE57346.2023.10144169
  2. 2. Vanhuysse, S., Georganos, S., Kuffer, M. M., Grippa, T., Lennert, M., & Wolff, E. (2021). Gridded Urban Deprivation Probability from Open Optical Imagery and Dual-Pol Sar Data. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS(11-16 July 2021: Brussels, Belgium) doi:10.1109/IGARSS47720.2021.9554231
  3. 3. Owusu, M., Kuffer, M. M., Belgiu, M., Grippa, T., Lennert, M., Georganos, S., & Vanhuysse, S. (2021). Geo-Ethics in Slum Mapping. doi:10.1109/IGARSS47720.2021.9553570
  4. 4. Linard, C., & Grippa, T. (2019). Refining intra-urban population mapping in sub-Saharan Africa: from land cover to land use. PERN Cyberseminar on Application of Gridded Population and Settlement Products in Geospatial Population-Environment Research doi:10.13140/RG.2.2.28836.42887
  5. 5. Lennert, M., Grippa, T., Radoux, J., Bassine, C., Beaumont, B., Defourny, P., & Wolff, E. (2019). Creating Wallonia's new very high resolution land cover maps: Combining GRASS GIS obia and OTB pixel-based results. The international archives of the photogrammetry, remote sensing and spatial information sciences,(Volume XLII-4/W14). doi:10.5194/isprs-archives-XLII-4-W14-151-2019
  6. 6. Grippa, T., Lennert, M., Georganos, S., Mboga, N. O., Vanhuysse, S., & Wolff, E. (2019). Mapping slums and model population density using earth observation data and open source solutions. In Proceedings of JURSE 2019 conference IEEE. doi:10.1109/JURSE.2019.8808934
  7. 7. Mboga, N. O., Georganos, S., Grippa, T., Lennert, M., Vanhuysse, S., & Wolff, E. (2019). Weakly supervised fully convolutional networks using OBIA classification output. In Proceedings of the 2019 Joint Urban Remote Sensing Event (JURSE) conference IEEE. doi:10.1109/JURSE.2019.8809000
  8. 8. Mboga, N. O., Georganos, S., Grippa, T., Lennert, M., Vanhuysse, S., & Wolff, E. (2018). Fully convolutional networks for the classification of historical panchromatic aerial photographs. Proceedings of the GEOBIA 2018 conference GEOBIA(2018: June 18-22, 2018: Montpellier)
  9. 9. Georganos, S., Grippa, T., Lennert, M., Vanhuysse, S., & Wolff, E. (2017). SPUSPO: Spatially Partitioned Unsupervised Segmentation Parameter Optimization for Efficiently Segmenting Large Heterogeneous Areas. Proceedings of the 2017 conference on Big Data from Space (BiDS’17) Big Data from Space(17: November 28-30, 2017: Toulouse, France)
  10. 10. Georganos, S., Grippa, T., Vanhuysse, S., Lennert, M., Shimoni, M., Wolff, E., et al. (2017). Optimizing classification performance in an object-based very-high-resolution land use-land cover urban application. In Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II SPIE. doi:10.1117/12.2278482
  11. 11. Grippa, T., Georganos, S., Vanhuysse, S., Lennert, M., & Wolff, E. (2017). A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery. Proceedings Volume 10431, Remote Sensing Technologies and Applications in Urban Environments II SPIE Remote Sensing(2017: Warsaw, Poland) doi:10.1117/12.2278422
  12. 12. Vanhuysse, S., Grippa, T., Lennert, M., Idrissa, M., & Wolff, E. (2017). Contribution of nDSM derived from VHR stereo imagery to urban land-cover mapping in Sub-Saharan Africa. In 2017 Joint Urban Remote Sensing Event (JURSE) IEEE. doi:10.1109/JURSE.2017.7924570
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