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RemoteCLIP: A Vision Language Foundation Model for Remote Sensing [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 General-purpose foundation models have led to recent breakthroughs in artificial intelligence (AI). In remote sensing, self-supervised learning (SSL) and masked image modeling (MIM) have been adopted to build foundation models.
F. Liu +5 more
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SpectralGPT: Spectral Remote Sensing Foundation Model [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner.
D. Hong +13 more
semanticscholar +1 more source
Remote Sensing Image Change Detection With Transformers [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 Modern change detection (CD) has achieved remarkable success by the powerful discriminative ability of deep convolutions. However, high-resolution remote sensing CD remains challenging due to the complexity of objects in the scene.
Hao Chen, Zipeng Qi, Zhenwei Shi
semanticscholar +1 more source
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation Based on Visual Foundation Model [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 Leveraging the extensive training data from SA-1B, the segment anything model (SAM) demonstrates remarkable generalization and zero-shot capabilities.
Keyan Chen +6 more
semanticscholar +1 more source
The Segment Anything Model (SAM) for Remote Sensing Applications: From Zero to One Shot [PDF]
International Journal of Applied Earth Observation and Geoinformation, 2023 Segmentation is an essential step for remote sensing image processing. This study aims to advance the application of the Segment Anything Model (SAM), an innovative image segmentation model by Meta AI, in the field of remote sensing image analysis.
L. Osco +6 more
semanticscholar +1 more source
RSGPT: A Remote Sensing Vision Language Model and Benchmark [PDF]
Isprs Journal of Photogrammetry and Remote Sensing, 2023 The emergence of large-scale large language models, with GPT-4 as a prominent example, has significantly propelled the rapid advancement of artificial general intelligence and sparked the revolution of Artificial Intelligence 2.0.
Yuan Hu +4 more
semanticscholar +1 more source
Remote Sensing, 2022 In the original article [...]
Remote Sensing Editorial Office
doaj +1 more source
Acknowledgment to Reviewers of Remote Sensing in 2021
Remote Sensing, 2022 Rigorous peer-reviews are the basis of high-quality academic publishing [...]
Remote Sensing Editorial Office
doaj +1 more source
Advancing Plain Vision Transformer Toward Remote Sensing Foundation Model [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Large-scale vision foundation models have made significant progress in visual tasks on natural images, with vision transformers (ViTs) being the primary choice due to their good scalability and representation ability.
Di Wang +6 more
semanticscholar +1 more source
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data [PDF]
IEEE International Conference on Computer Vision, 2021 Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use monitoring, or tackling climate change.
Oscar Mañas +4 more
semanticscholar +1 more source