| Appearance based deep domain adaptation for the classification of aerial images D Wittich, F Rottensteiner ISPRS Journal of Photogrammetry and Remote Sensing 180, 82-102, 2021 | 33 | 2021 |
| From silk to digital technologies: A gateway to new opportunities for creative industries, traditional crafts and designers. The SILKNOW case EA Pagán, MMG Salvatella, MD Pitarch, AL Muñoz, MMM Toledo, ... Sustainability 12 (19), 8279, 2020 | 21 | 2020 |
| Semantic segmentation of Brazilian savanna vegetation using high spatial resolution satellite data and U-net AK Neves, TS Körting, LMG Fonseca, CD Girolamo Neto, D Wittich, ... ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020 | 13 | 2020 |
| Adversarial domain adaptation for the classification of aerial images and height data using convolutional neural networks D Wittich, F Rottensteiner ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2019 | 12 | 2019 |
| Adversarial discriminative domain adaptation for deforestation detection J Noa, PJ Soto, G Costa, D Wittich, RQ Feitosa, F Rottensteiner ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2021 | 7 | 2021 |
| Automated segmentation of olivine phenocrysts in a volcanic rock thin section using a fully convolutional neural network A Leichter, RR Almeev, D Wittich, P Beckmann, F Rottensteiner, F Holtz, ... Frontiers in Earth Science 10, 740638, 2022 | 6 | 2022 |
| Deep domain adaptation by weighted entropy minimization for the classification of aerial images D Wittich ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020 | 6 | 2020 |
| Assessing the semantic similarity of images of silk fabrics using convolutional neural networks D Clermont, M Dorozynski, D Wittich, F Rottensteiner ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020 | 5 | 2020 |
| Improved classification of satellite imagery using spatial feature maps extracted from social media A Leichter, D Wittich, F Rottensteiner, M Werner, M Sester The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2018 | 5 | 2018 |
| Generating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes C Kruse, D Wittich, F Rottensteiner, C Heipke ISPRS Open Journal of Photogrammetry and Remote Sensing 5, 100017, 2022 | 4 | 2022 |
| From silk to digital technologies: A gateway to new opportunities for creative industries, traditional crafts and designers. The SILKNOW case E Alba Pagán, M Gaitán, MD Pitarch Garrido, A León Muñoz, ... | 4 | 2020 |
| Deep learning for the detection of early signs for forest damage based on satellite imagery D Wittich, F Rottensteiner, M Voelsen, C Heipke, S Müller ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2022 | 2 | 2022 |
| Deep Learning zur Analyse von Bildern von Seidenstoffen für Anwendungen im Kontext der Bewahrung des kulturellen Erbes M Dorozynski, D Wittich, F Rottensteiner Proceedings of the 39th Scientific-Technical Annual Meeting of the German …, 0 | 1 | |
| USING TIME SERIES IMAGE DATA TO IMPROVE THE GENERALIZATION CAPABILITIES OF A CNN–THE EXAMPLE OF DEFORESTATION DETECTION WITH SENTINEL-2 MX Ortega, D Wittich, F Rottensteiner, C Heipke, RQ Feitosa ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2023 | | 2023 |
| Deep Domain Adaptation for the Pixel-wise Classification of Aerial and Satellite Images DC Wittich Fachrichtung Geodäsie und Geoinformatik der Leibniz Unviersität Hannover, 2023 | | 2023 |
| Combining machine learning and petrology: application to the magma plumbing structure beneath Klyuchevskoy volcano, Kamchatka, Russia DRR DEGRAFFENRIED, A Leichter, R Almeev, D Wittich, MV Portnyagin, ... 2022 Goldschmidt Conference, 2022 | | 2022 |
| Wie schnell steigt Magma auf?: Maschinelles Lernen (ML) hilft bei der Antwort F Rottensteiner, F Holtz, R Almeev, DC Wittich, M Sester, A Leichter Unimagazin 1/2 (2022) 1, 42-44, 2022 | | 2022 |
| Artificial intelligence meets cultural heritage: Image classification for the prediction of semantic properties of silk fabrics M Dorozysnki, D Wittich, F Rottensteiner, D Clermont Weaving Europe Silk Heritage and digital technologies, 147-166, 2021 | | 2021 |
| Interdisciplinary Center for Applied Machine Learning-ICAML: 1.1 Schlussbericht der Leibniz Universität Hannover (LUH) A Leichter, M Sester, D Wittich, F Rottensteiner, M Werner Leibniz Universität Hannover (LUH), 2020 | | 2020 |
| Deep learning of topographic anomalies for the detection of re-gions of interest in 3D point clouds R Arav, D Wittich, F Rottensteiner VGC 23, 44, 0 | | |
