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The success of the Segment Anything Model (SAM) demonstrates the significance of data-centric machine learning.
Imagenet: A large-scale hierarchical image database
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Resunet-a: A deep learning framework for semantic segmentation of remotely sensed data
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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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Ye Lyu, George Vosselman, Gui-Song Xia, Alper Yilmaz, and Michael Ying Yang · 2020
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Land-cover classification with high-resolution remote sensing images using transferable deep models
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Parsing very high resolution urban scene images by learning deep convnets with edge-aware loss
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Object detection in aerial images: A large-scale benchmark and challenges
Jian Ding, Nan Xue, Gui-Song Xia, Xiang Bai, Wen Yang, Michael Yang, Serge Belongie, Jiebo Luo, Mihai Datcu, Marcello Pelillo, and Liangpei Zhang · 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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Keyan Chen, Chenyang Liu, Hao Chen, Haotian Zhang, Wenyuan Li, Zhengxia Zou, and Zhenwei Shi · 2023
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Vision transformer adapter for dense predictions
Zhe Chen, Yuchen Duan, Wenhai Wang, Junjun He, Tong Lu, Jifeng Dai, and Yu Qiao · 2023
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Ruining Deng, Can Cui, Quan Liu, Tianyuan Yao, Lucas W Remedios, Shunxing Bao, Bennett A Landman, Lee E Wheless, Lori A Coburn, Keith T Wilson, et al · 2023
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Knowledge distillation with segment anything (sam) model for planetary geological mapping
Sahib Julka and Michael Granitzer · 2023
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick · 2023
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Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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On creating benchmark dataset for aerial image interpretation: Reviews, guidances, and million-aid
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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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Loveda: A remote sensing land-cover dataset for domain adaptive semantic segmentation
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BEiT: BERT pre-training of image transformers
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Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2022
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Masked autoencoders are scalable vision learners
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Swin transformer embedding unet for remote sensing image semantic segmentation
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Grounding dino: Marrying dino with grounded pre-training for open-set object detection
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Segment anything in medical images
Jun Ma and Bo Wang · 2023
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The segment anything model (sam) for remote sensing applications: From zero to one shot
Lucas Prado Osco, Qiusheng Wu, Eduardo Lopes de Lemos, Wesley Nunes Gonçalves, Ana Paula Marques Ramos, Jonathan Li, and José Marcato Junior · 2023
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An empirical study of remote sensing pretraining
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Advancing plain vision transformer toward remote sensing foundation model
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Rongtao Xu, Changwei Wang, Jiguang Zhang, Shibiao Xu, Weiliang Meng, and Xiaopeng Zhang · 2023
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Text2seg: Remote sensing image semantic segmentation via text-guided visual foundation models
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Vitaev2: Vision transformer advanced by exploring inductive bias for image recognition and beyond
Qiming Zhang, Yufei Xu, Jing Zhang, and Dacheng Tao · 2023
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Personalize segment anything model with one shot
Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Peng Gao, and Hongsheng Li · 2023
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