An end-to-end framework for low-resolution remote sensing semantic segmentation
MB Pereira, JA dos Santos - 2020 IEEE Latin American GRSS …, 2020 - ieeexplore.ieee.org
High-resolution images for remote sensing applications are often not affordable or
accessible, especially when in need of a wide temporal span of recordings. Given the easy
access to low-resolution (LR) images from satellites, many remote sensing works rely on this
type of data. The problem is that LR images are not appropriate for semantic segmentation,
due to the need for high-quality data for accurate pixel prediction for this task. In this paper,
we propose an end-to-end framework that unites a super-resolution and a semantic …
accessible, especially when in need of a wide temporal span of recordings. Given the easy
access to low-resolution (LR) images from satellites, many remote sensing works rely on this
type of data. The problem is that LR images are not appropriate for semantic segmentation,
due to the need for high-quality data for accurate pixel prediction for this task. In this paper,
we propose an end-to-end framework that unites a super-resolution and a semantic …
An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation
M Barros Pereira, JA dos Santos - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
High-resolution images for remote sensing applications are often not affordable or
accessible, especially when in need of a wide temporal span of recordings. Given the easy
access to low-resolution (LR) images from satellites, many remote sensing works rely on this
type of data. The problem is that LR images are not appropriate for semantic segmentation,
due to the need for high-quality data for accurate pixel prediction for this task. In this paper,
we propose an end-to-end framework that unites a super-resolution and a semantic …
accessible, especially when in need of a wide temporal span of recordings. Given the easy
access to low-resolution (LR) images from satellites, many remote sensing works rely on this
type of data. The problem is that LR images are not appropriate for semantic segmentation,
due to the need for high-quality data for accurate pixel prediction for this task. In this paper,
we propose an end-to-end framework that unites a super-resolution and a semantic …
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