Related papers: Pluto's Surface Mapping using Unsupervised Learnin…
Global maps of Jupiter's atmospheric temperatures, gaseous composition and aerosol opacity are derived from a programme of 5-20 $\mu$m mid-infrared spectroscopic observations using the Texas Echelon Cross Echelle Spectrograph (TEXES) on…
The problem of unsupervised learning and segmentation of hyperspectral images is a significant challenge in remote sensing. The high dimensionality of hyperspectral data, presence of substantial noise, and overlap of classes all contribute…
Future telescopes will characterize rocky exoplanets in reflected light, revealing their albedo, which depends on surface, cloud, and atmospheric properties. Identifying these features is crucial for assessing habitability. We present…
Pluto and its satellites will be the most distant objects ever reconnoitered when NASA's New Horizons spacecraft conducts its intensive flyby of this system in 2015. The size-frequency distribution (SFD) of craters on the surfaces in the…
The New Horizons spacecraft carried three instruments that measured the space environment near Pluto as it flew by on 14 July 2015. The Solar Wind Around Pluto instrument revealed an interaction region confined sunward of Pluto to within…
Unsupervised feature selection (UFS) is an important task in data engineering. However, most UFS methods construct models from a single perspective and often fail to simultaneously evaluate feature importance and preserve their inherent…
With high-resolution spectroscopy we can study exoplanet atmospheres and learn about their chemical composition, temperature profiles, and presence of clouds and winds, mainly in hot, giant planets. State-of-the-art instrumentation is…
Accurate modeling of the Sun's coronal magnetic field and solar wind structures require inputs of the solar global magnetic field, including both the near and far sides, but the Sun's far-side magnetic field cannot be directly observed.…
We present a new method for the determination of the surface properties of airless bodies from measurements of the emitted infrared flux. Our approach uses machine learning techniques to train, validate, and test a neural network…
We present the results of an investigation using near-infrared spectra of Pluto taken on 72 separate nights using SpeX/IRTF. These data were obtained between 2001 and 2013 at various sub-observer longitudes. The aim of this work was to…
The largest trans-Neptunian objects (TNOs) represent an extremely diverse collection of primitive bodies in the outer solar system. The community typically refers to these objects as dwarf planets, though the IAU acknowledges only four TNOs…
Ground-penetrating radar (GPR) is a mature geophysical method that has gained increasing popularity in planetary science over the past decade. GPR has been utilised both for Lunar and Martian missions providing pivotal information regarding…
In this paper, we assess the scientific promise and technology feasibility of distributed instruments for planetary science. A distributed instrument is an instrument designed to collect spatially and temporally correlated data from…
Reconstructing open surfaces from multi-view images is vital in digitalizing complex objects in daily life. A widely used strategy is to learn unsigned distance functions (UDFs) by checking if their appearance conforms to the image…
We report results from monitoring Pluto's 0.8 to 2.4 {\mu}m reflectance spectrum with IRTF/SpeX on 65 nights over the dozen years from 2001 to 2012. The spectra show vibrational absorption features of simple molecules CH4, CO, and N2…
Using data from the Infrared Array Camera on the Spitzer Space Telescope, we present photometric observations of a sample of 100 trans-Neptunian objects (TNOs) beyond 2.2 {\mu}m. These observations, collected with two broad-band filters…
In this study, Cu-Cr composites were studied by nanoindentation. Arrays of indents were placed over large areas of the samples resulting in datasets consisting of several hundred measurements of Young's modulus and hardness at varying…
Unsupervised machine learning, and in particular data clustering, is a powerful approach for the analysis of datasets and identification of characteristic features occurring throughout a dataset. It is gaining popularity across scientific…
The field of autonomous navigation for unmanned ground vehicles (UGVs) is in continuous growth and increasing levels of autonomy have been reached in the last few years. However, the task becomes more challenging when the focus is on the…
The PLATO space mission is designed to detect telluric planets in the habitable zone of solar type stars, and simultaneously characterise the host star using ultra high precision photometry. The photometry will be performed on board using…