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Remote Sensing Image Analysis (RSiM) Group @ TU Berlin started in April, 2018. RSiM group performs research in the fields of processing and analysis of remote sensing images for Earth observation with interdisciplinary approaches associated to remote sensing, machine learning, signal&image processing and big data management.
Learning from Noisy Labels in Remote Sensing
December 19, 2020
To reduce the negative impact of noisy land-use and land-cover annotations, we research on developing noise robust deep learning models. We have recently made public our codes on noise robust deep learning models for Earth observation at noisy-labels-in-rs.org.
A New Project Funded by the Federal Ministry of Education and Research
June 14, 2020
RSiM is involved in a new project 'TreeSatAI-Künstliche Intelligenz mit Erdbeobachtungs- und Multi-Source Geodaten für das Infrastruktur-, Naturschutz- und Waldmonitoring' funded by the Federal Ministry of Education and Research for the period 2020-2022. The project partners are: Geoinformation in Environmental Planning Group of TU Berlin, LiveEO, LUP, DFKI and Vision Impulse.
Conference on Big Data and Machine Learning in Geosciences
January 24, 2020
The Federal Institute for Geosciences and Natural Resources (BGR), with the support of the German Federal Ministry of Economic Affairs and Energy (BMWi), organizes the International Conference on Big Data and Machine Learning in Geosciences that will be held on February 20-21, 2020 in Berlin. Prof. Demir is an invited speaker and will give a talk on ‘Deep Earth Query: Information Discovery from Big Earth Observation Data Archives’. Further information is available here.
The Trillion Pixel GeoAI Challenge Workshop at Oak Ridge National Laboratory
October 08, 2019
Prof. Demir was a panelist at the GeoAI workshop to discuss barriers, opportunities, and the way forward in exploiting high-resolution planetary imagery for greater societal impact. The highlight of this event was the presentations and discussions on societal AI challenges by experts from image science, computer vision, machine learning, high performance computing. Further information is available here.
Editorial Board Membership for the MDPI Remote Sensing Journal
July 12, 2019
Prof. Dr. Demir has been appointed as a member of the editorial board of "Remote Sensing Image Processing" section for the MDPI Remote Sensing journal.
A New Project Funded by the German Research Foundation
July 08, 2019
RSiM got a new project ‘IDEAL-VGI - Information Discovery from Big Earth Observation Data Archives by Learning from Volunteered Geographic Information’, which will be funded by the German Research Foundation for the period Oct. 2019-Oct. 2022. IDEAL-VGI is supported under the Priority Programme “Volunteered Geographic Information: Interpretation, Visualisation and Social Computing” [SPP 1894]).
BigEarthNet: A New Sentinel-2 Benchmark Archive
March 15, 2019
We have made public our BigEarthNet archive that is significantly larger than the existing archives in remote sensing and opens up promising directions to advance research for the analysis of large-scale remote sensing image archives.
2018 Early Career Award for Prof. Demir
July 27, 2018
Prof. Dr. Demir is the recipient of the prestigious “2018 Early Career Award” presented by the IEEE Geoscience and Remote Sensing Society (GRSS). IEEE GRSS founded in 1962 is the most important international scientific society in the field of geosciences and remote sensing. Factors considered for assigning the award are: quality, the significance and impact of contributions, papers published in archival journals, papers presented at conferences and symposia, a demonstration of leadership, and advancement of the profession.
New Starting at TU Berlin
April 13, 2018
The President, Prof. Dr. Thomsen welcomed all newly appointed professors at TU Berlin.
More information can be found at TUB-Pressestelle.
ERC Funded BigEarth Project Has Officially Started at TU Berlin
April 1, 2018
Prof. Dr. Begüm Demir moved with her BigEarth project from Italy to the TU Berlin. BigEarth is a research project funded by the European Research Council (ERC) Starting Grant, and it aims to develop a scalable and accurate Earth Observation (EO) image search and retrieval system for an accurate and fast discovery of crucial information for observing Earth from Big EO Archives.
For more details: www.tu-berlin.de
BigEarth project: bigearth.eu/index.html
Zusatzinformationen / Extras
Direktzugang:
Administration
Minh LeRaum EN 628
Phone +49 30 314 21418
sekr 'at' rsim.tu-berlin.de
Office Hours:
Tuesday and Thursday