Recent advances in multi-and hyperspectral image analysis
J Nalepa - Sensors, 2021 - mdpi.com
Current advancements in sensor technology bring new possibilities in multi-and
hyperspectral imaging. Real-life use cases which can benefit from such imagery span …
hyperspectral imaging. Real-life use cases which can benefit from such imagery span …
Multireceptive field: An adaptive path aggregation graph neural framework for hyperspectral image classification
Z Zhang, Y Ding, X Zhao, L Siye, N Yang, Y Cai… - Expert Systems with …, 2023 - Elsevier
In recent years, the applications of graph convolutional networks (GCNs) in hyperspectral
image (HSI) classification have attracted much attention. However, hyperspectral …
image (HSI) classification have attracted much attention. However, hyperspectral …
A comprehensive review on segmentation techniques for satellite images
Segmentation of satellite images is the noteworthy and essential step for better
understanding and analysis in various applications such as disaster and crisis management …
understanding and analysis in various applications such as disaster and crisis management …
Evaluating algorithms for anomaly detection in satellite telemetry data
Detecting anomalies in telemetry data captured on-board a spacecraft is critical to ensure its
safe operation. Although there exist various techniques for automatically detecting point …
safe operation. Although there exist various techniques for automatically detecting point …
Taking artificial intelligence into space through objective selection of hyperspectral earth observation applications: To bring the “brain” close to the “eyes” of satellite …
AM Wijata, MF Foulon, Y Bobichon… - … and Remote Sensing …, 2023 - ieeexplore.ieee.org
Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI)
bring exciting opportunities to various fields of science and industry that can directly benefit …
bring exciting opportunities to various fields of science and industry that can directly benefit …
Unsupervised segmentation of hyperspectral remote sensing images with superpixels
In this paper, we propose an unsupervised method for hyperspectral remote sensing image
segmentation. The method exploits the mean-shift clustering algorithm that takes as input a …
segmentation. The method exploits the mean-shift clustering algorithm that takes as input a …
Robust and reconfigurable on-board processing for a hyperspectral imaging small satellite
Hyperspectral imaging is a powerful remote sensing technology, but its use in space is
limited by the large volume of data it produces, which leads to a downlink bottleneck …
limited by the large volume of data it produces, which leads to a downlink bottleneck …
Squeezing adaptive deep learning methods with knowledge distillation for on-board cloud detection
Cloud detection is a pivotal satellite image pre-processing step that can be performed on
board a satellite to tag useful images. It can reduce the amount of data to downlink by …
board a satellite to tag useful images. It can reduce the amount of data to downlink by …
Benchmarking deep learning for on-board space applications
Benchmarking deep learning algorithms before deploying them in hardware-constrained
execution environments, such as imaging satellites, is pivotal in real-life applications …
execution environments, such as imaging satellites, is pivotal in real-life applications …
Early detection of Solanum lycopersicum diseases from temporally-aggregated hyperspectral measurements using machine learning
Some plant diseases can significantly reduce harvest, but their early detection in cultivation
may prevent those consequential losses. Conventional methods of diagnosing plant …
may prevent those consequential losses. Conventional methods of diagnosing plant …