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Unsupervised pre-training methods for large vision models have shown to enhance performance on downstream supervised tasks.
Using a time series of satellite imagery to detect land use and land cover changes in the atlanta, georgia metropolitan area
Xin Yang and CP Lo · 2002
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
Xingjian Shi, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
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Combining satellite imagery and machine learning to predict poverty
Neal Jean, Marshall Burke, Michael Xie, W Matthew Davis, David B Lobell, and Stefano Ermon · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deep gaussian process for crop yield prediction based on remote sensing data
Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, and Stefano Ermon · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Functional map of the world
Gordon Christie, Neil Fendley, James Wilson, and Ryan Mukherjee · 2018
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xview: Objects in context in overhead imagery
Darius Lam, Richard Kuzma, Kevin McGee, Samuel Dooley, Michael Laielli, Matthew Klaric, Yaroslav Bulatov, and Brendan McCord · 2018
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Spacenet: A remote sensing dataset and challenge series
Adam Van Etten, Dave Lindenbaum, and Todd M Bacastow · 2018
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Deep transfer learning for crop yield prediction with remote sensing data
Anna X Wang, Caelin Tran, Nikhil Desai, David Lobell, and Stefano Ermon · 2018
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Convolutional lstms for cloud-robust segmentation of remote sensing imagery
Marc Rußwurm and Marco Körner · 2018
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Psanet: Point-wise spatial attention network for scene parsing
Hengshuang Zhao, Yi Zhang, Shu Liu, Jianping Shi, Chen Change Loy, Dahua Lin, and Jiaya Jia · 2018
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Revisiting self-supervised visual representation learning
Alexander Kolesnikov, Xiaohua Zhai, and Lucas Beyer · 2019
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Self-supervised representation learning by rotation feature decoupling
Zeyu Feng, Chang Xu, and Dacheng Tao · 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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Semantic segmentation of crop type in africa: A novel dataset and analysis of deep learning methods
Rose M Rustowicz, Robin Cheong, Lijing Wang, Stefano Ermon, Marshall Burke, and David Lobell · 2019
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Temporal convolutional neural network for the classification of satellite image time series
Charlotte Pelletier, Geoffrey I Webb, and François Petitjean · 2019
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Predicting economic development using geolocated wikipedia articles
Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, Marshall Burke, David Lobell, and Stefano Ermon · 2019
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Learning to interpret satellite images using wikipedia
Burak Uzkent, Evan Sheehan, Chenlin Meng, Zhongyi Tang, Marshall Burke, David Lobell, and Stefano Ermon · 2019
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Land cover maps production with high resolution satellite image time series and convolutional neural networks: Adaptations and limits for operational systems
Andrei Stoian, Vincent Poulain, Jordi Inglada, Victor Poughon, and Dawa Derksen · 2019
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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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In-domain representation learning for remote sensing
Maxim Neumann, Andre Susano Pinto, Xiaohua Zhai, and Neil Houlsby · 2019
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Quantifying the carbon emissions of machine learning
Alexandre Lacoste, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres · 2019
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Contrastive multiview coding
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Sustainbench: Benchmarks for monitoring the sustainable development goals with machine learning
Christopher Yeh, Chenlin Meng, Sherrie Wang, Anne Driscoll, Erik Rozi, Patrick Liu, Jihyeon Lee, Marshall Burke, David B Lobell, and Stefano Ermon · 2021
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Spatial-temporal super-resolution of satellite imagery via conditional pixel synthesis
Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng, Marshall Burke, David Lobell, and Stefano Ermon · 2021
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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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Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data
Oscar Mañas, Alexandre Lacoste, Xavier Giro-i Nieto, David Vazquez, and Pau Rodriguez · 2021
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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, Jakob Uszkoreit, and Neil Houlsby · 2021
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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A survey on contrastive self-supervised learning
Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Debapriya Banerjee, and Fillia Makedon · 2020
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Self-supervised visual feature learning with deep neural networks: A survey
Longlong Jing and Yingli Tian · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
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Self-supervised equivariant attention mechanism for weakly supervised semantic segmentation
Yude Wang, Jie Zhang, Meina Kan, Shiguang Shan, and Xilin Chen · 2020
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Compress: Self-supervised learning by compressing representations
Soroush Abbasi Koohpayegani, Ajinkya Tejankar, and Hamed Pirsiavash · 2020
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Panoptic segmentation of satellite image time series with convolutional temporal attention networks
Vivien Sainte Fare Garnot and Loic Landrieu · 2021
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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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Self-supervised learning of remote sensing scene representations using contrastive multiview coding
Vladan Stojnic and Vladimir Risojevic · 2021
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Multi-modal self-supervised representation learning for earth observation
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Semantic segmentation of remote sensing images with self-supervised multitask representation learning
Wenyuan Li, Hao Chen, and Zhenwei Shi · 2021
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Geographical knowledge-driven representation learning for remote sensing images
Wenyuan Li, Keyan Chen, Hao Chen, and Zhenwei Shi · 2021
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Training data-efficient image transformers & distillation through attention
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Vivit: A video vision transformer
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Ze Liu, Jia Ning, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin, and Han Hu · 2021
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An empirical study of training self-supervised vision transformers
Xinlei Chen*, Saining Xie*, and Kaiming He · 2021
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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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Tracking urbanization in developing regions with remote sensing spatial-temporal super-resolution
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Is-count: Large-scale object counting from satellite images with covariate-based importance sampling
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Multimae: Multi-modal multi-task masked autoencoders
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Building coverage estimation with low-resolution remote sensing imagery
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