7 papers
Beam Index Map Prediction in Unseen Environments from Geospatial Data
Fabian Jaensch, Giuseppe Caire, Begüm Demir
In 5G, beam training consists of the efficient association of users to beams for a given beamforming codebook used at the base station and the given propagation environment in the…
Sea-Undistort: A Dataset for Through-Water Image Restoration in High Resolution Airborne Bathymetric Mapping
Maximilian Kromer, Panagiotis Agrafiotis, Begüm Demir
Accurate image-based bathymetric mapping in shallow waters remains challenging due to the complex optical distortions such as wave induced patterns, scattering and sunglint, introd…
Adjustable Spatio-Spectral Hyperspectral Image Compression Network
Martin Hermann Paul Fuchs, Behnood Rasti, Begüm Demir
With the rapid growth of hyperspectral data archives in remote sensing (RS), the need for efficient storage has become essential, driving significant attention toward learning-base…
On the Effectiveness of Methods and Metrics for Explainable AI in Remote Sensing Image Scene Classification
Jonas Klotz, Tom Burgert, Begüm Demir
The development of explainable artificial intelligence (xAI) methods for scene classification problems has attracted great attention in remote sensing (RS). Most xAI methods and th…
Continual Self-Supervised Learning with Masked Autoencoders in Remote Sensing
Lars Möllenbrok, Behnood Rasti, Begüm Demir
The development of continual learning (CL) methods, which aim to learn new tasks in a sequential manner from the training data acquired continuously, has gained great attention in…
A Plasticity-Aware Method for Continual Self-Supervised Learning in Remote Sensing
Lars Möllenbrok, Behnood Rasti, Begüm Demir
Continual self-supervised learning (CSSL) methods have gained increasing attention in remote sensing (RS) due to their capability to learn new tasks sequentially from continuous st…