1 citations · 3 across the 5 of their papers we have counts for
5 papers
Multi-Modal Vision Transformers for Crop Mapping from Satellite Image Time Series
Theresa Follath, David Mickisch, Jan Hemmerling +3
Using images acquired by different satellite sensors has shown to improve classification performance in the framework of crop mapping from satellite image time series (SITS). Exist…
Transformer-based Multi-Modal Learning for Multi Label Remote Sensing Image Classification
David Hoffmann, Kai Norman Clasen, Begüm Demir
In this paper, we introduce a novel Synchronized Class Token Fusion (SCT Fusion) architecture in the framework of multi-modal multi-label classification (MLC) of remote sensing (RS…
LiT-4-RSVQA: Lightweight Transformer-based Visual Question Answering in Remote Sensing
Leonard Hackel, Kai Norman Clasen, Mahdyar Ravanbakhsh +1
Visual question answering (VQA) methods in remote sensing (RS) aim to answer natural language questions with respect to an RS image. Most of the existing methods require a large am…
Learning Across Decentralized Multi-Modal Remote Sensing Archives with Federated Learning
Barış Büyüktaş, Gencer Sumbul, Begüm Demir
The development of federated learning (FL) methods, which aim to learn from distributed databases (i.e., clients) without accessing data on clients, has recently attracted great at…
Satellite Image Search in AgoraEO
Ahmet Kerem Aksoy, Pavel Dushev, Eleni Tzirita Zacharatou +5
The growing operational capability of global Earth Observation (EO) creates new opportunities for data-driven approaches to understand and protect our planet. However, the current…