activity
20202026
most citedMulti-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification

47 citations · 64 across the 13 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.CV2025

REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware Agent

Binger Chen, Tacettin Emre Bök, Behnood Rasti +2

Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and multimodal architectures. FMs are adapted…

eess.SP2025

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…

eess.IV2025★ 1 cited

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…

cs.CV2025★ 3 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

Self-Supervised Cross-Modal Text-Image Time Series Retrieval in Remote Sensing

Genc Hoxha, Olivér Angyal, Begüm Demir

The development of image time series retrieval (ITSR) methods is a growing research interest in remote sensing (RS). Given a user-defined image time series (i.e., the query time se…