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Evaluating and Benchmarking Foundation Models for Earth Observation and
  Geospatial AI

Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AI

26 June 2024
Nikolaos Dionelis
Casper Fibaek
Luke Camilleri
Andreas Luyts
Jente Bosmans
B. L. Saux
ArXivPDFHTML

Papers citing "Evaluating and Benchmarking Foundation Models for Earth Observation and Geospatial AI"

4 / 4 papers shown
Title
CARE: Confidence-Aware Regression Estimation of building density fine-tuning EO Foundation Models
CARE: Confidence-Aware Regression Estimation of building density fine-tuning EO Foundation Models
Nikolaos Dionelis
Jente Bosmans
Nicolas Longepe
53
0
0
19 Feb 2025
Learning from Unlabelled Data with Transformers: Domain Adaptation for
  Semantic Segmentation of High Resolution Aerial Images
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images
Nikolaos Dionelis
Francesco Pro
Luca Maiano
Irene Amerini
B. L. Saux
34
2
0
17 Apr 2024
Lightweight, Pre-trained Transformers for Remote Sensing Timeseries
Lightweight, Pre-trained Transformers for Remote Sensing Timeseries
Gabriel Tseng
Ruben Cartuyvels
Ivan Zvonkov
Mirali Purohit
David Rolnick
Hannah Kerner
72
59
0
27 Apr 2023
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial
  Representation Learning
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Colorado Reed
Ritwik Gupta
Shufan Li
S. Brockman
Christopher Funk
Brian Clipp
Kurt Keutzer
Salvatore Candido
M. Uyttendaele
Trevor Darrell
113
165
0
30 Dec 2022
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