Dr. Hao Li

E-Mail: hao_bgd.li@tum.de
Telefon: (+49) 89 289 555 54
Raum: 103
Anschrift: Technische Universität München
Dr. Hao Li
Lise-Meitner-Str. 9
85521 Ottobrunn
Full publications and CV

Publikationen an der Professur

  1. Liu, Z., Fang, C., Li, H., Wu, J., Zhou, L., & Werner, M. (2024). Efficiency and equality of the multimodal travel between public transit and bike-sharing accounting for multiscale. Sustainable Cities and Society, 101, 105096. https://doi.org/https://doi.org/10.1016/j.scs.2023.105096 [PDF] [Online] [BibTeX]
  2. Luo, X., Walther, P., Mansour, W., Teuscher, B., Zollner, J. M., Li, H., & Werner, M. (2023). Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet. The 31st ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’23), November 13–16, 2023, Hamburg, Germany. https://doi.org/10.1145/3589132.3629971 [PDF] [Online] [BibTeX]
  3. Hong, D., Zhang, B., Li, H., Li, Y., Yao, J., Li, C., Werner, M., Chanussot, J., Zipf, A., & Zhu, X. X. (2023). Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks. Remote Sensing of Environment, 299, 113856. https://doi.org/https://doi.org/10.1016/j.rse.2023.113856 [Online] [BibTeX]
  4. Li, H., Wang, J., Zollner, J. M., Mai, G., Lao, N., & Werner., M. (2023). Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: A Case Study of OpenStreetMap Missing Building Detection in Africa. Proceedings of the 31st International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/3589132.3625598 [PDF] [Online] [BibTeX]
  5. Werner, M., Li, H., Zollner, J. M., Teuscher, B., & Deuser., F. (2023). Bavaria Buildings - A Novel Dataset for Building Footprint Extraction, Instance Segmentation, and Data Quality Estimation (Data and Resources Paper). Proceedings of the 31st International Conference on Advances in Geographic Information Systems (ACM SIGSPATAIL GIS’23). https://doi.org/10.1145/3589132.3625658 [PDF] [Online] [BibTeX]
  6. Liu, Z., Wu, J., Li, H., & Werner, M. (2023). Spatio-temporal Analysis of Urban Economic Resilience during Covid-19 with Multilayer Complex Networks. The ISPRS Geospatial Week 2023, GeoHB Workshop. [PDF] [BibTeX]
  7. Li, H., Yuan, Z., Dax, G., Kong, G., Fan, H., Zipf, A., & Werner, M. (2023). Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation. In R. Beecham, J. A. Long, D. Smith, Q. Zhao, & S. Wise (Eds.), 12th International Conference on Geographic Information Science (GIScience 2023) (Vol. 277, pp. 7:1–7:15). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.GIScience.2023.7 [PDF] [Online] [BibTeX]
  8. Teuscher, B., Geißendörfer, O., Luo, X., Li, H., Anders, K., Holst, C., & Werner, M. (2024). Efficient In-Memory Point Cloud Query Processing. In T. H. Kolbe, A. Donaubauer, & C. Beil (Eds.), Recent Advances in 3D Geoinformation Science (pp. 267–286). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43699-4_16 [PDF] [Online] [BibTeX]
  9. Xiong, Z., Stober, D., Krstić, M., Korup, O., Arango, M. I., Li, H., & Werner, M. (2023). Integrating AI Hardware in Academic Teaching: Experiences and Scope from Brandenburg and Bavaria. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. [BibTeX]
  10. Knoblauch, S., Li, H., Lautenbach, S., Elshiaty, Y., Rocha, A. A. de A., Resch, B., Arifi, D., Jänisch, T., Morales, I., & Zipf, A. (2023). Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti. International Journal of Applied Earth Observation and Geoinformation, 119, 103304. https://doi.org/10.1016/j.jag.2023.103304 [PDF] [Online] [BibTeX]
  11. Dax, G., Nagarajan, S., Li, H., & Werner, M. (2022). Compression Supports Spatial Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). https://doi.org/10.1109/JSTARS.2022.3226563 [Online] [BibTeX]
  12. Grinberger, A. Y., Liu, P., Li, H., Juhasz, L., & Minghini, M. (2022). OpenStreetMap, beyond just Data: The Academic Track at State of the Map 2022. Zenodo. https://doi.org/10.5281/zenodo.7004424 [Online] [BibTeX]
  13. Werner, M., & Li, H. (2022). AtlasHDF: An Efficient Big Data Framework for GeoAI. 1–7. https://doi.org/10.1145/3557917.3567615 [PDF] [Online] [BibTeX]
  14. Hu, X., Zhou, Z., Li, H., Hu, Y., Gu, F., Kersten, J., Fan, H., & Klan, F. (2023). Location Reference Recognition from Texts: A Survey and Comparison. ACM Comput. Surv. https://doi.org/10.1145/3625819 [Online] [BibTeX]

Andere Publikationen

  1. Li, H., Zech, J., Hong, D., Ghamisi, P., Schultz, M., & Zipf, A. (2022). Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection. International Journal of Applied Earth Observation and Geoinformation, 110, 102804. [BibTeX]
  2. Li, H., Zech, J., Ludwig, C., Fendrich, S., Shapiro, A., Schultz, M., & Zipf, A. (2021). Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning. International Journal of Applied Earth Observation and Geoinformation, 104, 102571. [BibTeX]
  3. Li, H., Yuan, Z., Novack, T., Huang, W., & Zipf, A. (2022). Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing. Computers, Environment and Urban Systems, 96, 101848. [BibTeX]
  4. Li, H., Ghamisi, P., Rasti, B., Wu, Z., Shapiro, A., Schultz, M., & Zipf, A. (2020). A multi-sensor fusion framework based on coupled residual convolutional neural networks. Remote Sensing, 12(12), 2067. [BibTeX]
  5. Li, H., Ghamisi, P., Soergel, U., & Zhu, X. X. (2018). Hyperspectral and LiDAR fusion using deep three-stream convolutional neural networks. Remote Sensing, 10(10), 1649. [BibTeX]
  6. Li, H., Herfort, B., Huang, W., Zia, M., & Zipf, A. (2020). Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 41–51. [BibTeX]
  7. Li, H., Herfort, B., Lautenbach, S., Chen, J., & Zipf, A. (2022). Improving OpenStreetMap missing building detection using few-shot transfer learning in sub-Saharan Africa. Transactions in GIS. [BibTeX]

© 2020 M. Werner