Reiterer, A., Wäschle, K., Störk, D., Leydecker, A., & Gitzen, N. [ca. 2020]. Fully automated segmentation of 2 D and 3 D mobile mapping data for reliable modeling of surface structures using deep learning [Cd]. Freiburg: Universität. https://doi.org/10.3390/rs12162530
ISO-690 (author-date, English)REITERER, Alexander, WÄSCHLE, Katharina, STÖRK, Dominik, LEYDECKER, Achim und GITZEN, Niko, 2020. Fully automated segmentation of 2 D and 3 D mobile mapping data for reliable modeling of surface structures using deep learning. Freiburg: Universität.
Modern Language Association 9th editionReiterer, A., K. Wäschle, D. Störk, A. Leydecker, und N. Gitzen. Fully automated segmentation of 2 D and 3 D mobile mapping data for reliable modeling of surface structures using deep learning. cd, Universität, 2020, https://doi.org/10.3390/rs12162530.
Mohr Siebeck - Recht (Deutsch - Österreich)Reiterer, Alexander/Wäschle, Katharina/Störk, Dominik/Leydecker, Achim/Gitzen, Niko: Fully automated segmentation of 2 D and 3 D mobile mapping data for reliable modeling of surface structures using deep learning, Freiburg 2020.
Emerald - HarvardReiterer, A., Wäschle, K., Störk, D., Leydecker, A. und Gitzen, N. (2020), Fully automated segmentation of 2 D and 3 D mobile mapping data for reliable modeling of surface structures using deep learning, Bd. , Universität, Freiburg, verfügbar unter:https://doi.org/10.3390/rs12162530.