9 citations · 9 across the 4 of their papers we have counts for
4 papers
Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data
Daniel Kovac, Jan Mucha, Jon Alvarez Justo +7
This article explores the latest Convolutional Neural Networks (CNNs) for cloud detection aboard hyperspectral satellites. The performance of the latest 1D CNN (1D-Justo-LiuNet) an…
Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison
Daniela Lupu, Joseph L. Garrett, Tor Arne Johansen +2
Dimensionality reduction can be applied to hyperspectral images so that the most useful data can be extracted and processed more quickly. This is critical in any situation in which…
A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction
Jon Alvarez Justo, Daniela Lupu, Milica Orlandic +2
Hyperspectral Imaging comprises excessive data consequently leading to significant challenges for data processing, storage and transmission. Compressive Sensing has been used in th…
An Open Hyperspectral Dataset with Sea-Land-Cloud Ground-Truth from the HYPSO-1 Satellite
Jon A. Justo, Joseph Garrett, Dennis D. Langer +3
Hyperspectral Imaging, employed in satellites for space remote sensing, like HYPSO-1, faces constraints due to few labeled data sets, affecting the training of AI models demanding…