Jonathan Prexl

According to our database1, Jonathan Prexl authored at least 15 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Data.
CoRR, April, 2026

2025
Sensor-Informed Self-Supervised Representation Learning for Multi-Modal Earth Observation Data.
PhD thesis, 2025

SARFormer - An Acquisition Parameter Aware Vision Transformer for Synthetic Aperture Radar Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024
Global OpenBuildingMap - Unveiling the Mystery of Global Buildings.
CoRR, 2024

Sensor Parameter Encoding for Multi-Sensor Self-Supervised Learning via Masked Autoencoders.
Proceedings of the IGARSS 2024, 2024

Mapping High-Resolution Building Development Over Delhi Ncr Using Sentinel-2.
Proceedings of the IGARSS 2024, 2024

SenPa-MAE: Sensor Parameter Aware Masked Autoencoder for Multi-satellite Self-supervised Pretraining.
Proceedings of the Pattern Recognition, 2024

2023
Data-Centric Machine Learning for Geospatial Remote Sensing Data.
CoRR, 2023

The Potential of Sentinel-2 Data for Global Building Footprint Mapping with High Temporal Resolution.
Proceedings of the Joint Urban Remote Sensing Event, 2023

High Precision Mapping Of Building Changes Using Sentinel-2.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

The Effect of Contrastive Pretraining on Downstream Tasks in Optical Remote Sensing.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Multi-Modal Multi-Objective Contrastive Learning for Sentinel-1/2 Imagery.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021
Mitigating Spatial and Spectral Differences for Change Detection Using Super-Resolution and Unsupervised Learning.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Using Machine Learning to predict extreme events in the Hénon map.
CoRR, 2020

Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping - Challenges and Opportunities.
CoRR, 2020


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