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Found 6 papers, 1 papers with code
One-Shot Initial Orbit Determination in Low-Earth Orbit
Due to the importance of satellites for society and the exponential increase in the number of objects in orbit, it is important to accurately determine the state (e. g., position and velocity) of these Resident Space Objects (RSOs) at any time and in a timely manner.
Probability of Collision of satellites and space debris for short-term encounters: Rederivation and fast-to-compute upper and lower bounds
It is estimated that, in orbit, there are millions of fragments a few millimeters in size and thousands of inoperative satellites and discarded rocket stages.
Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses
Extracting information from radiofrequency (RF) signals using artificial neural networks at low energy cost is a critical need for a wide range of applications from radars to health.
Probabilistic Registration for Gaussian Process 3D shape modelling in the presence of extensive missing data
We propose a shape fitting/registration method based on a Gaussian Processes formulation, suitable for shapes with extensive regions of missing data.
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL
The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly.
From noisy point clouds to complete ear shapes: unsupervised pipeline
Ears are a particularly difficult region of the human face to model, not only due to the non-rigid deformations existing between shapes but also to the challenges in processing the retrieved data.
