Superresolution

Deep learning-based harmonization and super-resolution of Landsat-8 and Sentinel-2 images, 17 May. 2024 (papers)
Our paper Deep learning-based harmonization and super-resolution of Landsat-8 and Sentinel-2 images, which is based on the masters thesis of my colleague Venkatesh Thirugnana Sambandham, has been published in the ISPRS Journal of Photogrammetry and Remote Sensing. This work is an extension of our previous workshop paper on transformers for satellite homogenization. In summary, we find that a simple UNet model provides surprisingly good performance for the satellite homogenization task. We …
Categories: Deep Learning
344 Words, Tagged with: Deep Learning · Superresolution
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Towards Transformer-based Homogenization of Satellite Imagery for Landsat-8 and Sentinel-2, 13 Aug. 2022 (papers)
Our abstract Towards Transformer-based Homogenization of Satellite Imagery for Landsat-8 and Sentinel-2 was accepted for presentation on the Transformers Workshop for Environmental Science. In summary, we somewhat surprisingly found that transformers, a neural network architecture that achieves state-of-the-art results on most tasks it is applied to, does not outperform a vanilla U-Net model on our particular superresolution task.
Categories: Deep Learning
58 Words, Tagged with: ESST · Superresolution
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