Yu Feng

Arbeitete als wissenschaftlicher Mitarbeiter in einem vom BMBF geförderten Projekt (EVUS) an der Nutzung von Daten aus Sozialen Medien, um daraus Hinweise auf Überschwemmungen und Hochwasser zu finden. Hierzu setzte er Methoden des Deep Learnings ein.

 

 

Publikationen

Begutachtete Zeitschriftenartikel und Buchkapitel

  • Yu Feng, Qing Xiao, Claus Brenner, Aaron Peche, Juntao Yang, Udo Feuerhake, Monika Sester (2022): Determination of building flood risk maps from LiDAR mobile mapping dataComputers, Environment and Urban Systems, Volume 93, 2022
    DOI: 10.1016/j.compenvurbsys.2022.101759
    ISSN: 0198-9715
  • V. Rözer, A. Peche, S. Berkhahn, Y. Feng, L. Fuchs, T. Graf, U. Haberlandt, H. Kreibich, R. Sämann, M. Sester, B. Shehu, J. Wahl, I. Neuweiler (2021): Impact‐based forecasting for pluvial floodsEarth's Future, e2020EF001851.
    DOI: 10.1029/2020EF001851
  • Feng, Y., Brenner, C., & Sester, M. (2020): Flood severity mapping from Volunteered Geographic Information by interpreting water level from images containing people: A case study of Hurricane HarveyISPRS Journal of Photogrammetry and Remote Sensing, 169, 301-319.
    DOI: 10.1016/j.isprsjprs.2020.09.011
    arXiv: 2006.11802
  • Feng, Y., Thiemann, F., & Sester, M. (2019): Learning Cartographic Building Generalization with Deep Convolutional Neural NetworksISPRS Int. J. Geo-Inf. 2019, 8(6), 258
    DOI: 10.3390/ijgi8060258
  • Feng, Y. and M. Sester (2018): Extraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photosISPRS International Journal of Geo-Information 7(2),39
    DOI: 10.3390/ijgi7020039

Begutachtete Konferenzbeiträge

  • Vinu Kamalasanan, Yu Feng, and Monika Sester. (2022): IMPROVING 3D PEDESTRIAN DETECTION FOR WEARABLE SENSOR DATA WITH 2D HUMAN POSEISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 4 (2022): 219-226. | File |
  • Feng, Y., Brenner, C., & Sester, M. (2020): Learning a Precipitation Indicator from Traffic Speed Variation PatternsTransportation Research Procedia, 47, 203-210.
    DOI: 10.1016/j.trpro.2020.03.090
  • Feng, Y., Brenner, C., & Sester, M. (2018): Enhancing the resolution of urban digital terrain models using mobile mapping systemsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W6 (2018), S. 11-18.
    DOI: 10.5194/isprs-annals-IV-4-W6-11-2018
  • Feng, Y., M. Sester (2017): Social media as a rainfall indicatorBregt, A., Sarjakoski, T., Lammeren, R. van, Rip, F. (Eds.). Societal Geo-Innovation : short papers, posters and poster abstracts of the 20th AGILE Conference on Geographic Information Science | File |

Konferenzbeiträge

  • Feng, Y., Yang, C., & Sester, M. (2020): Multi-scale Building Maps from Aerial ImageryInternational Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 41-47.
    DOI: 10.5194/isprs-archives-XLIII-B3-2020-41-2020
  • Feng, Y., Tang, S., Cheng, H., Sester, M. (2019): Flood level estimation from news articles and flood detection from satellite image sequencesWorking Notes Proceedings of the MediaEval 2019 Workshop, Sophia-Antipolis, France, 27-29 October 2019. More Info
  • Feng, Y., Shebotnov, S., Brenner, C., Sester, M. (2018): Ensembled convolutional neural network models for retrieving flood relevant tweetsWorking Notes Proceedings of the MediaEval 2018 Workshop, Sophia Antipolis, France, 29-31 October 2018. More Info
  • Fuchs, L. Graf, T., Haberlandt, U. Kreibich, H., Neuweiler, I. Sester, M. Berkhahn, S. Feng, Y. Peche, A., Rözer, V., Sämann, R.; Shehu, B., Wahl, J. (2018): Echtzeitvorhersage urbaner Sturzfluten und damit verbundene WasserkontaminationenAquaUrbanica 2018, Schriftenreihe Wasser Infrastruktur Ressourcen, Band 1, TU Kaiserslautern. | File |
  • Sester, M., Feng, Y., & Thiemann, F. (2018): Building Generalization using Deep LearningInt. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 565-572, 2018.
    DOI: 10.5194/isprs-archives-XLII-4-565-2018
  • Fuchs, L., T. Graf, U. Haberlandt, H. Kreibich, I. Neuweiler, M. Sester, S. Berkhahn, Y. Feng, A. Peche, V. Rözer, R. Sämann, B. Shehu, J. Wahl (2017): Real-Time Prediction of Pluvial Floods and Induced Water Contamination17th International Conference on Urban Drainage, 9/2017, Prague | File |
  • Feng, Y. and Schlichting, A. and Brenner, C. (2016): 3D feature point extraction from LiDAR data using a neural networkISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLI-B1, pp. 563-569
    DOI: 10.5194/isprs-archives-XLI-B1-563-2016

Monographien

  • Yu Feng (2021): Extraction of Flood and Precipitation Observations from Opportunistic Volunteered Geographic InformationDeutsche Geodätische Kommission bei der Bayerischen Akademie der Wissenschaften Reihe C, Dissertationen, Heft Nr. 882, München 2021 More Info
    ISBN: 978-3-7696-5294-9
    ISSN: 0065-5325

Diskussionspapier

  • Hao Cheng, Li Feng, Hailong Liu, Takatsugu Hirayama, Hiroshi Murase, Monika Sester (2021): Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with AttentionArXiv More Info
    arXiv: 2105.03891

sonstige Beiträge

  • Viktor Rözer, Aaron Peche, Simon Berkhahn, Yu Feng, Lothar Fuchs, Thomas Graf, Uwe Haberlandt, Heidi Kreibich, Robert Sämann, Monika Sester, Bora Shehu, Julian Wahl, Insa Neuweiler (2020): Impact-based early warning for pluvial floodsEGU General Assembly Conference Abstracts (p. 10507)
  • Fuchs, L. Graf, T., Haberlandt, U. Kreibich, H., Neuweiler, I. Sester, M. Berkhahn, S. Feng, Y. Peche, A., Rözer, V., Sämann, R.; Shehu, B., Wahl, J. (2018): Echtzeitvorhersage von Überflutung, Schadstofftransport und Schäden für Sturzflutereignisse am Beispiel Oberricklingen in HannoverForum für Hydrologie und Wasserbewirtschaftung, Heft 40, 2018 | File |