In this paper, we present a novel deep learning-based imputation technique for inferring spectral values under the clouds using nearby cloud-free satellite ...
In this paper, we present a novel deep learning-based imputation technique for inferring spectral values under the clouds using nearby cloud-free satellite ...
In this paper, we present a novel deep learning-based imputation technique for inferring spectral values under the clouds using nearby cloud-free satellite ...
Some of these sequenceto-point approaches impose tight restrictions on the maximum cloud coverage per image, e.g., [33] require at most 10-30% cloud cover, and ...
Aug 24, 2023 · We present a knowledge-guided harmonization model that maps the reflectance response from one satellite collection to another based on the spectral ...
Deep Residual Network with Multi-Image Attention for Imputing Under Clouds in Satellite Imagery , 2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION ...
Zhao, and R. R. Vatsavai, “Deep residual network with multi-image attention for imputing under clouds in satellite imagery,” in 2022 27th International ...
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A new benchmark data set consisting of images from two widely used and publicly available satellite images, Landsat-8 and Sentinel-2, and a new multi-stream ...
Deep Residual Network with Multi-Image Attention for Imputing Under Clouds in Satellite Imagery · Xian Yang · Yifan Zhao · Ranga Raju Vatsavai.
This model is an accurate and robust model for the semantic segmentation of clouds in satellite imagery, and the model achieves state-of-the-art performance.
Missing: Multi- Imputing