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Large, self-supervised vision models have led to substantial advancements for automatically interpreting natural images.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Deep learning in remote sensing: A comprehensive review and list of resources
Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia, Liangpei Zhang, Feng Xu, and Friedrich Fraundorfer · 2017
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Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth · 2019
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Tile2vec: Unsupervised representation learning for spatially distributed data
Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell, and Stefano Ermon · 2019
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Deep learning in remote sensing applications: A meta-analysis and review
Lei Ma, Yu Liu, Xueliang Zhang, Yuanxin Ye, Gaofei Yin, and Brian Alan Johnson · 2019
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Deep learning and process understanding for data-driven earth system science
Markus Reichstein, Gustau Camps-Valls, Bjorn Stevens, Martin Jung, Joachim Denzler, and Nuno Carvalhais · 2019
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Bigearthnet: A large-scale benchmark archive for remote sensing image understanding
Gencer Sumbul, Marcela Charfuelan, Begüm Demir, and Volker Markl · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Deep unsupervised embedding for remotely sensed images based on spatially augmented momentum contrast
Jian Kang, Ruben Fernandez-Beltran, Puhong Duan, Sicong Liu, and Antonio J Plaza · 2020
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Remote sensing image scene classification with self-supervised paradigm under limited labeled samples
Chao Tao, Ji Qi, Weipeng Lu, Hao Wang, and Haifeng Li · 2020
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What should not be contrastive in contrastive learning
Tete Xiao, Xiaolong Wang, Alexei A Efros, and Trevor Darrell · 2020
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Geography-aware self-supervised learning
Kumar Ayush, Burak Uzkent, Chenlin Meng, Kumar Tanmay, Marshall Burke, David Lobell, and Stefano Ermon · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Using satellite imagery to understand and promote sustainable development
Marshall Burke, Anne Driscoll, David B Lobell, and Stefano Ermon · 2021
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Self-supervised sar-optical data fusion of sentinel-1/-2 images
Yuxing Chen and Lorenzo Bruzzone · 2021
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Multi-modal self-supervised representation learning for earth observation
Pallavi Jain, Bianca Schoen-Phelan, and Robert Ross · 2021
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Toward foundation models for earth monitoring: Proposal for a climate change benchmark
Alexandre Lacoste, Evan David Sherwin, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, et al · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data
Oscar Manas, Alexandre Lacoste, Xavier Giró-i Nieto, David Vazquez, and Pau Rodriguez · 2021
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Global and local contrastive self-supervised learning for semantic segmentation of hr remote sensing images
Haifeng Li, Yi Li, Guo Zhang, Ruoyun Liu, Haozhe Huang, Qing Zhu, and Chao Tao · 2022
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Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning
Colorado J Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Salvatore Candido, Matt Uyttendaele, and Trevor Darrell · 2022
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Automated extraction of energy systems information from remotely sensed data: A review and analysis
Simiao Ren, Wayne Hu, Kyle Bradbury, Dylan Harrison-Atlas, Laura Malaguzzi Valeri, Brian Murray, and Jordan M Malof · 2022
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Torchgeo: deep learning with geospatial data
Adam J Stewart, Caleb Robinson, Isaac A Corley, Anthony Ortiz, Juan M Lavista Ferres, and Arindam Banerjee · 2022
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Representation learning for remote sensing: An unsupervised sensor fusion approach
Aidan M Swope, Xander H Rudelis, and Kyle T Story · 2021
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Satlas: A large-scale, multi-task dataset for remote sensing image understanding
Favyen Bastani, Piper Wolters, Ritwik Gupta, Joe Ferdinando, and Aniruddha Kembhavi · 2022
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Machine learning in weather prediction and climate analyses—applications and perspectives
Bogdan Bochenek and Zbigniew Ustrnul · 2022
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Self-supervised encoders are better transfer learners in remote sensing applications
Zachary D Calhoun, Saad Lahrichi, Simiao Ren, Jordan M Malof, and Kyle Bradbury · 2022
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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
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Masked auto-encoding spectral–spatial transformer for hyperspectral image classification
Damian Ibanez, Ruben Fernandez-Beltran, Filiberto Pla, and Naoto Yokoya · 2022
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Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham, Lichao Mou, and Xiao Xiang Zhu · 2022
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Meter-ml: A multi-sensor earth observation benchmark for automated methane source mapping
Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y Liu, Andrew Y Ng, and Robert B Jackson · 2022
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Longlora: Efficient fine-tuning of long-context large language models
Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, and Jiaya Jia · 2023
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Revisiting pre-trained remote sensing model benchmarks: resizing and normalization matters
Isaac Corley, Caleb Robinson, Rahul Dodhia, Juan M Lavista Ferres, and Peyman Najafirad · 2023
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Gfm: Building geospatial foundation models via continual pretraining
Matias Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, and Mu Li · 2023
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Considerations for ai-eo for agriculture in sub-saharan africa
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Climax: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, and Aditya Grover · 2023
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Masked vision transformers for hyperspectral image classification
Linus Scheibenreif, Michael Mommert, and Damian Borth · 2023
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Lightweight, pre-trained transformers for remote sensing timeseries
Gabriel Tseng, Ivan Zvonkov, Mirali Purohit, David Rolnick, and Hannah Kerner · 2023
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