Torben Peters – Institute of Cartography and Geoinformatics

Arbeitete als wissenschaftlicher Mitarbeiter im DFG-Graduiertenkollege i.c.sens. Er forschte über die automatische Klassifikation von Punktwolken in semantisch bedeutsame Objekte. Hierzu nutzte er die Farbinformation aus den Bilddaten.

Publikationen

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Begutachtete Zeitschriftenartikel und Buchkapitel

Peters, T., Brenner, C., & Schindler, K. (2023): Semantic segmentation of mobile mapping point clouds via multi-view label transfer, ISPRS Journal of Photogrammetry and Remote Sensing, 202, 30-39.
Malinovskaya, A., Otto, P., Peters, T. (2022): Statistical learning for change point and anomaly detection in graphs, Artificial Intelligence, Big Data and Data Science in Statistics (pp. 85-109). Springer, Cham.
arXiv: 2011.06080
Maneejuk, P., Peters, T., Brenner, C., & Kreinovich, V. (2022): How to Train A-to-B and B-to-A Neural Networks So That the Resulting Transformations Are (Almost) Exact Inverses, In: Credible Asset Allocation, Optimal Transport Methods, and Related Topics (pp. 203-209). Cham: Springer International Publishing.
Peters T. und Brenner C. (2020): Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering, PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science
DOI: 10.1007/s41064-020-00114-z
Steffen Schön, Claus Brenner, Hamza Alkhatib, Max Coenen, Hani Dbouk, Nicolas Garcia-Fernandez, Colin Fischer, Christian Heipke, Katja Lohmann, Ingo Neumann, Uyen Nguyen, Jens-André Paffenholz, Torben Peters, Franz Rottensteiner, Julia Schachtschneider, Monika Sester, Ligang Sun, Sören Vogel, Raphael Voges und Bernardo Wagner (2018): Integrity and Collaboration in Dynamic Sensor Networks, Sensors (Basel, Switzerland) 18.7.
DOI: http://www.mdpi.com/1424-8220/18/7/2400

Begutachtete Konferenzbeiträge

Peters, T., Schindler, K., & Brenner, C. (2022): Self-Supervised Adversarial Shape Completion, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2, 143-150.
DOI: https://doi.org/10.5194/isprs-annals-V-2-2022-143-2022
Peters, T., Brenner, C. (2018): Conditional Adversarial Networks for Multimodal Photo-Realistic Point Cloud Rendering, Spatial Big Data and Machine Learning in GIScience, GIScience Workshop 2018 More info

Konferenzbeiträge

Koetsier, C., Peters, T., & Sester, M. (2020): Learning the 3D Pose of Vehicles from 2D Vehicle Patches, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 683-688.
DOI: 10.5194/isprs-archives-XLIII-B2-2020-683-2020
Peters, T., Brenner, C., & Song, M. (2020): Improving Deep Learning based Semantic Segmentation with Multi View Outlier Correction, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 711-716.
DOI: 10.5194/isprs-archives-XLIII-B2-2020-711-2020
Peters, T. & C. Brenner (2019): Automatic Generation of Large Point Cloud Training Datasets Using Label Transfer, 39. Wissenschaftlich-Technische Jahrestagung der DGPF e.V., 20. – 22. Februar 2019 in Wien, Thomas P. Kersten (Hrsg.) | File |
ISBN: ISSN 0942-2870