1 code implementation • 17 Jan 2024 • Konrad Heidler, Ingmar Nitze, Guido Grosse, Xiao Xiang Zhu
To improve model generalization across the Arctic without the need for additional labelled data, we present a semi-supervised learning approach to train semantic segmentation models to detect RTS.
no code implementations • 7 Jul 2023 • Konrad Heidler, Lichao Mou, Erik Loebel, Mirko Scheinert, Sébastien Lefèvre, Xiao Xiang Zhu
Building on this observation, we completely rephrase the task as a contour tracing problem and propose a model for explicit contour detection that does not incorporate any dense predictions as intermediate steps.
1 code implementation • 2 Aug 2021 • Konrad Heidler, Lichao Mou, Di Hu, Pu Jin, Guangyao Li, Chuang Gan, Ji-Rong Wen, Xiao Xiang Zhu
By fine-tuning the models on a number of commonly used remote sensing datasets, we show that our approach outperforms existing pre-training strategies for remote sensing imagery.
Ranked #2 on Cross-Modal Retrieval on SoundingEarth
1 code implementation • 22 Apr 2021 • Yuansheng Hua, Lichao Moua, Jianzhe Lin, Konrad Heidler, Xiao Xiang Zhu
To be more specific, we first learn the prototype representation of each aerial scene from single-scene aerial image datasets and store it in an external memory.
5 code implementations • 2 Mar 2021 • Konrad Heidler, Lichao Mou, Celia Baumhoer, Andreas Dietz, Xiao Xiang Zhu
Deep learning-based coastline detection algorithms have begun to outshine traditional statistical methods in recent years.