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The multi-modal remote sensing foundation model (MM-RSFM) has significantly advanced various Earth observation tasks, such as urban planning, environmental monitoring, and natural disaster management.
Adaptive mixtures of local experts
Robert A. Jacobs, Michael I. Jordan, Steven J. Nowlan, and Geoffrey E. Hinton · 1991
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey E. Hinton · 2008
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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A survey on object detection in optical remote sensing images
Gong Cheng and Junwei Han · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Fully convolutional networks for dense semantic labelling of high-resolution aerial imagery
Jamie Sherrah · 2016
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Remote sensing image scene classification: Benchmark and state of the art
Gong Cheng, Junwei Han, and Xiaoqiang Lu · 2017
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 2017
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Aid: A benchmark data set for performance evaluation of aerial scene classification
Gui-Song Xia, Jingwen Hu, Fan Hu, Baoguang Shi, Xiang Bai, Yanfei Zhong, Liangpei Zhang, and Xiaoqiang Lu · 2017
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Urban change detection for multispectral earth observation using convolutional neural networks
Rodrigo Caye Daudt, Bertr Le Saux, Alexandre Boulch, and Yann Gousseau · 2018
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Unified perceptual parsing for scene understanding
Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, and Jian Sun · 2018
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Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images
Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, and Xiaoning Qian · 2019
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High-quality cloud masking of landsat 8 imagery using convolutional neural networks
M. Joseph Hughes and Robert H. Kennedy · 2019
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Bigearthnet: A large-scale benchmark archive for remote sensing image understanding
Gencer Sumbul, Jian Kang, Tristan Kreuziger, Filipe Marcelino, Hugo Costa, Pedro Benevides, Mario Caetano, and Begüm Demir · 2019
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isaid: A large-scale dataset for instance segmentation in aerial images
Syed Waqas Zamir, Aditya Arora, Akshita Gupta, Salman Khan, Guolei Sun, Fahad Shahbaz Khan, Fan Zhu, Ling Shao, Gui-Song Xia, and Xiang Bai · 2019
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A spatial-temporal attention-based method and a new dataset for remote sensing image change detection
Hao Chen and Zhenwei Shi · 2020
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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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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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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Unsupervised domain adaptation using a teacher-student network for cross-city classification of sentinel-2 images
Jingliang Hu, Lichao Mou, and Xiao Xiang Zhu · 2020
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Object detection in optical remote sensing images: A survey and a new benchmark
Ke Li, Gang Wan, Gong Cheng, Liqiu Meng, and Junwei Han · 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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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Remote sensing image change detection with transformers
Hao Chen, Zipeng Qi, and Zhenwei Shi · 2021
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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam M. Shazeer · 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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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Satlaspretrain: A large-scale dataset for remote sensing image understanding
Favyen Bastani, Piper Wolters, Ritwik Gupta, Joe Ferdinando, and Aniruddha Kembhavi · 2023
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A multi-scale weakly supervised learning method with adaptive online noise correction for high-resolution change detection of built-up areas
Yinxia Cao, Xin Huang, and Qihao Weng · 2023
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A billion-scale foundation model for remote sensing images
Keumgang Cha, Junghoon Seo, and Taekyung Lee · 2023
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Croma: Remote sensing representations with contrastive radar-optical masked autoencoders
Anthony Fuller, Koreen Millard, and James R. Green · 2023
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Unitr: A unified and efficient multi-modal transformer for bird’s-eye-view representation
Wang Haiyang, Tang Hao, Shi Shaoshuai, Li Aoxue, Li Zhenguo, Schiele Bernt, and Liwei Wang · 2023
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Scaling vision with sparse mixture of experts
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, and Neil Houlsby · 2021
Cited alongside, same era.
BigEarthNet-MM: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval
Gencer Sumbul, Arne de Wall, Tristan Kreuziger, Filipe Marcelino, Hugo Costa, Pedro Benevides, Mario Caetano, Begüm Demir, and Volkerl Mark · 2021
Cited alongside, same era.
Graph adversarial self-supervised learning
Longqi Yang, Liangliang Zhang, and Wenjing Yang · 2021
Cited alongside, same era.
A review of deep learning methods for semantic segmentation of remote sensing imagery
Xiaohui Yuan, Jianfang Shi, and Lichuan Gu · 2021
Cited alongside, same era.
Uni-perceiver: Pre-training unified architecture for generic perception for zero-shot and few-shot tasks
Xizhou Zhu, Jinguo Zhu, Hao Li, Xiaoshi Wu, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, and Jifeng Dai · 2021
Cited alongside, same era.
Self-supervised material and texture representation learning for remote sensing tasks
Peri Akiva, Matthew Purri, and Matthew Leotta · 2022
Cited alongside, same era.
Anchor-free oriented proposal generator for object detection
Gong Cheng, Jiabao Wang, Ke Li, Xingxing Xie, Chunbo Lang, Yanqing Yao, and Junwei Han · 2022
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Seeing beyond the patch: Scale-adaptive semantic segmentation of high-resolution remote sensing imagery based on reinforcement learning
Yinhe Liu, Sunan Shi, Junjue Wang, and Yanfei Zhong · 2023
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Change-aware sampling and contrastive learning for satellite images
Utkarsh Mall, Bharath Hariharan, and Kavita Bala · 2023
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Towards geospatial foundation models via continual pretraining
Matías Mendieta, Boran Han, Xingjian Shi, Yi Zhu, Chen Chen, and Mu Li · 2023
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Cmid: A unified self-supervised learning framework for remote sensing image understanding
Dilxat Muhtar, Xueliang Zhang, Pengfeng Xiao, Zhenshi Li, and Feng Gu · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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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, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, and Trevor Darrell · 2023
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Mixture-of-experts meets instruction tuning: A winning combination for large language models
Sheng Shen, Le Hou, Yan-Quan Zhou, Nan Du, S. Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, and Denny Zhou · 2023
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Tov: The original vision model for optical remote sensing image understanding via self-supervised learning
Chao Tao, Ji Qi, Guo Zhang, Qing Zhu, Weipeng Lu, and Haifeng Li · 2023
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Xinye Wanyan, Sachith Seneviratne, Shuchang Shen, and Michael Kirley · 2023
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A comprehensive survey of oriented object detection in remote sensing images
Long Wen, Yu Cheng, Yi Fang, and Xinyu Li · 2023
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Meta-transformer: A unified framework for multimodal learning
Yiyuan Zhang, Kaixiong Gong, Kaipeng Zhang, Hongsheng Li, Yu Qiao, Wanli Ouyang, and Xiangyu Yue · 2023
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AnySat: An Earth observation model for any resolutions, scales, and modalities
Guillaume Astruc, Nicolas Gonthier, Clement Mallet, and Loic Landrieu · 2024
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Vision transformers need registers
Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2024
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Skysense: A multi-modal remote sensing foundation model towards universal interpretation for earth observation imagery
Xin Guo, Jiangwei Lao, Bo Dang, Yingying Zhang, Lei Yu, Lixiang Ru, Liheng Zhong, Ziyuan Huang, Kang Wu, Dingxiang Hu, Huimei He, Jian Wang, Jingdong Chen, Ming Yang, Yongjun Zhang, and Yansheng Li · 2024
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Bridging remote sensors with multisensor geospatial foundation models
Boran Han, Shuai Zhang, Xingjian Shi, and Markus Reichstein · 2024
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Spectralgpt: Spectral remote sensing foundation model
Danfeng Hong, Bing Zhang, Xuyang Li, Yuxuan Li, Chenyu Li, Jing Yao, Pedram Ghamisi, Naoto Yokoya, Hao Li, Xiuping Jia, Antonio Plaza, Paolo Gamba, Jon Atli Benediktsson, and Jocelyn Chanussot · 2024
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Task-customized masked autoencoder via mixture of cluster-conditional experts
Zhili Liu, Kai Chen, Jianhua Han, Lanqing Hong, Hang Xu, Zhenguo Li, and James Tin-Yau Kwok · 2024
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Rethinking transformers pre-training for multi-spectral satellite imagery
Mubashir Noman, Muzammal Naseer, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, and Fahad Shahbaz Khan · 2024
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Mixture-of-experts meets instruction tuning: A winning combination for large language models
Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, and Denny Zhou · 2024
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One for all: Toward unified foundation models for earth vision
Zhitong Xiong, Yi Wang, Fahong Zhang, and Xiao Xiang Zhu · 2024
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