Related papers: SPACE-SUIT: An Artificial Intelligence Based Chrom…

We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by…

Exploring high-latitude lunar regions presents an extremely challenging visual environment for robots. The low sunlight elevation angle and minimal light scattering result in a visual field dominated by a high dynamic range featuring long,…

We give an overview and describe the rationale, methods, and testing of the Hubble Space Telescope (HST) Archival Legacy project "SKYSURF." SKYSURF uses HST's unique capability as an absolute photometer to measure the ~0.2-1.7 $\mu$m sky…

The acoustic resonator is an important model for explaining the three-minute oscillations in the chromosphere above sunspot umbrae. The steep temperature gradients at the photosphere and transition region provide the cavity for the acoustic…

Solar flares are among the most severe space weather phenomena, and they have the capacity to generate radiation storms and radio disruptions on Earth. The accurate prediction of solar flare events remains a significant challenge, requiring…

We describe the application of Semantic Segmentation by using the Self Organizing Map technique to an high spatial and spectral resolution dataset acquired along the H$\alpha$ line at 656.28 nm by the Interferometric Bi-dimensional…

We present results using the AutoClass analysis application available at NASA/Ames Intelligent Systems Div. (2002) which is a Bayesian, finite mixture model classification system developed by Cheeseman and Stutz (1996). We apply this system…

We present the development of SIR-HUXt, the integration of a sequential importance resampling (SIR) data assimilation scheme with the HUXt solar wind model. SIR-HUXt is designed to assimilate the time-elongation profiles of CME fronts in…

The observations of solar photosphere from the ground encounter significant problems due to the presence of Earth's turbulent atmosphere. Prior to applying image reconstruction techniques, the frames obtained in most favorable atmospheric…

The characterization of the optical properties of the atmosphere in the near UV, in particular the tropospheric aerosol stratification, clouds optical depth and spatial distribution are common in the field of atmospheric physics, due to…

Next-generation solar spectrographs increasingly record dense wavelength windows in which tens to hundreds of spectral lines are sampled at each spatial location and time step. This expands the scope for multi-line, multi-height diagnostics…

Statistical weak lensing by large-scale structure -- cosmic shear -- is a promising cosmological tool, which has motivated the design of several large upcoming surveys. Here, we present a measurement of cosmic shear using coadded Sloan…

This study introduces a laboratory experiment designed to assess the influence of annotation strategies, levels of imbalanced data, and prior experience, on the performance of human annotators. The experiment focuses on labeling aerial…

Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features.…

Spectral type recognition is an important and fundamental step of large sky survey projects in the data reduction for further scientific research, like parameter measurement and statistic work. It tends out to be a huge job to manually…

Outdoor scene parsing models are often trained on ideal datasets and produce quality results. However, this leads to a discrepancy when applied to the real world. The quality of scene parsing, particularly sky classification, decreases in…

With the growing amount of astronomical data, there is an increasing need for automated data processing pipelines, which can extract scientific information from observation data without human interventions. A critical aspect of these…

Despite extensive searches and the relative proximity of solar system objects (SSOS) to Earth, many remain undiscovered and there is still much to learn about their properties and interactions. This work is the first in a series dedicated…

In this paper, we propose SPACE, a novel anomaly detection methodology that integrates a Feature Encoder (FE) into the structure of the Student-Teacher method. The proposed method has two key elements: Spatial Consistency regularization…

We present a new galaxy cluster search in the COSMOS field through the use of the Adaptive Matched Identifier of Clustered Objects (AMICO). We produced a new cluster and group catalogue up to $z=2$, by performing an innovative application…