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Found 6 papers, 2 papers with code
Fast model inference and training on-board of Satellites
In this work we demonstrate the reliable use of RaVAEn onboard a satellite, achieving an encoding time of 0. 110s for tiles of a 4. 8x4. 8 km$^2$ area.
Cloud detection machine learning algorithms for PROBA-V
This paper presents the development and implementation of a cloud detection algorithm for Proba-V.
Convolutional Neural Networks for Multispectral Image Cloud Masking
Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems.
Estimating Crop Primary Productivity with Sentinel-2 and Landsat 8 using Machine Learning Methods Trained with Radiative Transfer Simulations
Satellite remote sensing has been widely used in the last decades for agricultural applications, {both for assessing vegetation condition and for subsequent yield prediction.}
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection
In addition, the training of the proposed adversarial domain adaptation model can be modified to improve the performance in a specific remote sensing application, such as cloud detection, by including a dedicated term in the cost function.
Fair Kernel Learning
It has been shown that not including sensitive features that bias fairness, such as gender or race, is not enough to mitigate the discrimination when other related features are included.
