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Deep learning models are increasingly data-hungry, requiring significant resources to collect and compile the datasets needed to train them, with Earth Observation (EO) models being no exception.
“Imagenet classification with deep convolutional neural networks,”
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton, · 2012
Earlier work this paper cites.
“LUCAS Soil, the largest expandable soil dataset for europe: a review,”
A. Orgiazzi, C. Ballabio, P. Panagos, A. Jones, and O. Fernández-Ugalde, · 2018
Earlier work this paper cites.
“Bigearthnet: A large-scale benchmark archive for remote sensing image understanding,”
Gencer Sumbul, Marcela Charfuelan, Begüm Demir, and Volker Markl, · 2019
Earlier work this paper cites.
“Multisensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery,”
Patrick Ebel, Andrea Meraner, Michael Schmitt, and Xiao Xiang Zhu, · 2020
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“Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data,”
Oscar Mañas, Alexandre Lacoste, Xavier Giró i Nieto, David Vázquez, and Pau Rodríguez López, · 2021
Earlier work this paper cites.
“RapidAI4EO: A corpus for higher spatial and temporal reasoning,”
Giovanni B. Marchisio, Patrick Helber, Benjamin Bischke, Timothy Davis, Çaglar Senaras, Daniele Zanaga, Ruben Van De Kerchove, and Annett Wania, · 2021
Earlier work this paper cites.
“LAION-5B: An open large-scale dataset for training next generation image-text models,”
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade W Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa R Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev, · 2022
Earlier work this paper cites.
“High-resolution image synthesis with latent diffusion models,”
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer, · 2022
Cited alongside, same era.
“Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,”
Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David Lobell, and Stefano Ermon, · 2022
Cited alongside, same era.
“SEN12MS-CR-TS: A remote sensing data set for multi-modal multi-temporal cloud removal,”
Patrick Ebel, Yajin Xu, Michael Schmitt, and Xiaoxiang Zhu, · 2022
Cited alongside, same era.
“CloudSEN12, a global dataset for semantic understanding of cloud and cloud shadow in sentinel-2,”
Cesar Aybar, Luis Ysuhuaylas, Jhomira Loja, Karen Gonzales, Fernando Herrera, Lesly Bautista, Roy Yali, Angie Flores, Lissette Diaz, Nicole Cuenca, Wendy Espinoza, Fernando Prudencio, Valeria Llactayo, David Montero, Martin Sudmanns, Dirk Tiede, Gonzalo Mateo-García, and Luis Gómez-Chova, · 2022
Cited alongside, same era.
“Open high-resolution satellite imagery: The WorldStrat dataset – with application to super-resolution,”
Julien Cornebise, Ivan Orsolic, and Freddie Kalaitzis, · 2022
“Copernicus sentinel data access annual report 2022,”
Adriana Grazia Castriotta and Federica Volpi, · 2023
Later among the works it cites.
“From LAION-5B to LAION-EO: Filtering billions of images using anchor datasets for satellite image extraction,”
Mikolaj Czerkawski and Alistair Francis, · 2023
Later among the works it cites.
“SatCLIP: Global, general-purpose location embeddings with satellite imagery,”
Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, and Marc Rußwurm, · 2023
Later among the works it cites.
“Remote sensing vision-language foundation models without annotations via ground remote alignment,”
Utkarsh Mall, Cheng Perng Phoo, Meilin Kelsey Liu, Carl Vondrick, Bharath Hariharan, and Kavita Bala, · 2023
Later among the works it cites.
“There are no data like more data: Datasets for deep learning in earth observation,”
Michael Schmitt, Seyed Ali Ahmadi, Yonghao Xu, Gülşen Taşkin, Ujjwal Verma, Francescopaolo Sica, and Ronny Hänsch, · 2023
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Cited alongside, same era.
“Satlaspretrain: A large-scale dataset for remote sensing image understanding,”
Favyen Bastani, Piper Wolters, Ritwik Gupta, Joe Ferdinando, and Aniruddha Kembhavi, · 2022
Cited alongside, same era.
“SEnSeI: A deep learning module for creating sensor independent cloud masks,”
Alistair Francis, John Mrziglod, Panagiotis Sidiropoulos, and Jan-Peter Muller, · 2022
Cited alongside, same era.
Later among the works it cites.
“EarthNets: An open deep learning platform for earth observation,”
Z. Xiong and X. X. Zhu, · 2023
Later among the works it cites.
“SSL4EO-S12: A large-scale multimodal, multitemporal dataset for self-supervised learning in earth observation [software and data sets],”
Yi Wang, Nassim Ait Ali Braham, Zhitong Xiong, Chenying Liu, Conrad M. Albrecht, and Xiao Xiang Zhu, · 2023
Later among the works it cites.