| HED-UNet: Combined segmentation and edge detection for monitoring the Antarctic coastline K Heidler, L Mou, C Baumhoer, A Dietz, XX Zhu IEEE Transactions on Geoscience and Remote Sensing 60, 1-14, 2021 | 48 | 2021 |
| Developing and testing a deep learning approach for mapping retrogressive thaw slumps I Nitze, K Heidler, S Barth, G Grosse Remote Sensing 13 (21), 4294, 2021 | 15 | 2021 |
| Self-supervised audiovisual representation learning for remote sensing data K Heidler, L Mou, D Hu, P Jin, G Li, C Gan, JR Wen, XX Zhu International Journal of Applied Earth Observation and Geoinformation 116 …, 2023 | 11 | 2023 |
| Aerial scene understanding in the wild: Multi-scene recognition via prototype-based memory networks Y Hua, L Mou, J Lin, K Heidler, XX Zhu ISPRS Journal of Photogrammetry and Remote Sensing 177, 89-102, 2021 | 10 | 2021 |
| Remote sensing for assessing drought insurance claims in central europe K Heidler, A Fietzke IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 3 | 2019 |
| Seeing the bigger picture: Enabling large context Windows in neural networks by combining multiple zoom levels K Heidler, L Mou, XX Zhu 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 3033 …, 2021 | 2 | 2021 |
| Extracting Glacier Calving Fronts by Deep Learning: The Benefit of Multispectral, Topographic, and Textural Input Features E Loebel, M Scheinert, M Horwath, K Heidler, J Christmann, LD Phan, ... IEEE Transactions on Geoscience and Remote Sensing 60, 1-12, 2022 | 1 | 2022 |
| Evaluating a deep-learning approach for mapping retrogressive thaw slumps across the Arctic I Nitze, K Heidler, S Barth, A Targowicka, G Grosse AGU Fall Meeting Abstracts 2021, B51B-05, 2021 | 1 | 2021 |
| IceLines–A new data set of Antarctic ice shelf front positions CA Baumhoer, AJ Dietz, K Heidler, C Kuenzer Scientific Data 10 (1), 138, 2023 | | 2023 |
| Towards pan-Arctic glacier calving front variability with deep learning T Li, K Heidler, L Mou, A Igneczi, X Zhu, J Bamber EGU23, 2023 | | 2023 |
| Data product of Greenland glacier calving front locations delineated by deep learning, 2013 to 2021 E Loebel, M Scheinert, M Horwath, A Humbert, J Sohn, K Heidler, ... Technische Universität Dresden, 2023 | | 2023 |
| Towards a Deep-Learning based Inventory of Retrogressive Thaw Slumps across the Arctic I Nitze, K Heidler, S Barth, P Bernhard, K Maier, G Grosse | | 2022 |
| Deep Active Contour Models for Delineating Glacier Calving Fronts K Heidler, L Mou, E Loebel, M Scheinert, S Lefèvre, XX Zhu IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022 | | 2022 |
| Deep Learning for mapping retrogressive thaw slumps across the Arctic I Nitze, K Heidler, S Barth, G Grosse | | 2022 |
| Deep learning for mapping retrogressive thaw slumps and landslides across the Arctic permafrost domain I Nitze, K Heidler, S Barth, G Grosse | | 2022 |
| IceLines-A new service to monitor Antarctic ice shelf front dynamics CA Baumhoer, AJ Dietz, K Heidler, C Kuenzer EGU General Assembly Conference Abstracts, EGU22-3402, 2022 | | 2022 |
| Manually delineated glacier calving fronts of 23 Greenland and 2 Antarctic outlet glaciers from 2013 to 2021 and source code for automated extraction by deep learning E Loebel, M Scheinert, M Horwath, K Heidler, J Christmann, LD Phan, ... Technische Universität Dresden, 2022 | | 2022 |
| The AI-CORE Project-Artificial Intelligence for Cold Regions C Baumhoer, A Dietz, K Heidler, XX Zhu, M Scheinert, E Loebel, I Nitze, ... | | 2022 |
| Status of the Artificial Intelligence for Cold Regions (AI-CORE) project-data integration and method implementation on the infrastructures A Dietz, C Baumhoer, K Heidler, LC Mou, I Nitze, M Scheinert, T Dinter, ... | | 2021 |
| HED-UNet: A Multi-Scale Framework for Simultaneous Segmentation and Edge Detection K Heidler, L Mou, C Baumhoer, A Dietz, XX Zhu 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 3037 …, 2021 | | 2021 |
Xiao Xiang ZhuTechnical University of MunichVerified email at tum.de
