Big Data Analytics for Earth Observation
Data Management and Machine Learning for Earth Observation
The mission of the Senior Research Group led by Prof. Dr. Begüm Demir is to develop innovative AI-driven solutions for diverse earth observation (EO) problems. With advances in satellite technology, EO data archives are continuously growing with high speed, delivering an unprecedented amount of data on the state of our planet over time. For example, via the Copernicus Programme – the European flagship satellite initiative in EO – Sentinel satellites acquire roughly 12 terabyte (TB) of satellite images per day, and the total size of the Copernicus data archives is almost 20 petabytes (PB). The “big EO data” is a great source of information that is relevant for several varying EO applications, as for example climate change analysis, urban area studies, forestry applications, risk and damage assessment, water quality assessment or crop monitoring. To address challenging problems in this field, the research activities of this group lie at the intersection of remote sensing, data management and machine learning.
Gencer Sumbul, Begüm Demir
Generative Reasoning Integrated Label Noise Robust Deep Image Representation Learning
Martin Hermann Paul Fuchs, Begüm Demir
HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods
Leonard Hackel, Kai Norman Clasen, Mahdyar Ravanbakhsh, Begüm Demir
LIT-4-RSVQA: Lightweight Transformer-based Visual Question Answering in Remote Sensing
David Hoffmann, Kai Norman Clasen, Begüm Demir
Transformer-based Multi-Modal Learning for Multi-Label Remote Sensing Image Classification
Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Sašo Džeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider
Artificial intelligence to advance Earth observation: a perspective
Research from the very top
BIFOLD scientist Prof. Dr. Begüm Demir explains the benefits of using Explainable Artificial Intelligence (XAI) to enhance earth observation satellite data analysis in the Tagesspiegel TU Berlin supplement.
Photo recap: All Hands Meeting 2023
On October 9 and 10, 2023, BIFOLD welcomed the other Geman AI centers (ScaDS.AI Dresden/Leipzig, Lamarr Institute, Tübingen AI Center, MCML, and the DFKI) in Berlin. The annual meeting featured guests, partners, visitors, and researchers from all over Germany.
AI centers are the foundation of the German AI ecosystem
On October 9th and 10th, 2023, the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin invited scientists from the university AI competence centers (BIFOLD, ScaDS.AI Dresden/Leipzig, Lamarr Institute, Tübingen AI Center, and MCML) and the DFKI to Berlin to present and discuss the latest results of their research on the EUREF campus.
Research Group Lead
Doctoral Researcher
Doctoral researcher
Doctoral Researcher
Student Assistant
Doctoral Researcher