Zobrazeno 1 - 10
of 1 090
pro vyhledávání: '"GOMEZ, PABLO"'
Autor:
Plumridge, Meghan, Maråk, Rasmus, Ceccobello, Chiara, Gómez, Pablo, Meoni, Gabriele, Svoboda, Filip, Lane, Nicholas D.
Segmentation of Earth observation (EO) satellite data is critical for natural hazard analysis and disaster response. However, processing EO data at ground stations introduces delays due to data transmission bottlenecks and communication windows. Usin
Externí odkaz:
http://arxiv.org/abs/2411.17831
Autor:
Gómez, Pablo, Vavrek, Roland D., Buenadicha, Guillermo, Hoar, John, Kruk, Sandor, Reerink, Jan
State-of-the-art space science missions increasingly rely on automation due to spacecraft complexity and the costs of human oversight. The high volume of data, including scientific and telemetry data, makes manual inspection challenging. Machine lear
Externí odkaz:
http://arxiv.org/abs/2411.05596
Publikováno v:
Proceedings of SPAICE2024 (2024) 241-246
Rapid progress in the capabilities of machine learning approaches in natural language processing has culminated in the rise of large language models over the last two years. Recent works have shown unprecedented adoption of these for academic writing
Externí odkaz:
http://arxiv.org/abs/2406.17324
Autor:
Dima, Elisabeta-Iulia, Gómez, Pablo, Kruk, Sandor, Kretschmar, Peter, Rosen, Simon, Popa, Călin-Adrian
Reflected or scattered light produce artefacts in astronomical observations that can negatively impact the scientific study. Hence, automated detection of these artefacts is highly beneficial, especially with the increasing amounts of data gathered.
Externí odkaz:
http://arxiv.org/abs/2406.17323
Autor:
Sahlmann, Johannes, Gómez, Pablo
The third Gaia data release (DR3) contains $\sim$170 000 astrometric orbit solutions of two-body systems located within $\sim$500 pc of the Sun. Determining component masses in these systems, in particular of stars hosting exoplanets, usually hinges
Externí odkaz:
http://arxiv.org/abs/2404.09350
Autor:
Pérez-Pérez, Juan F., Gómez, Pablo Isaza, Bonet, Isis, Sánchez-Pinzón, María Solange, Caraffini, Fabio, Lochmuller, Christian
Climate risk assessment is becoming increasingly important. For organisations, identifying and assessing climate-related risks is challenging, as they can come from multiple sources. This study identifies and assesses the main climate transition risk
Externí odkaz:
http://arxiv.org/abs/2404.16055
Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient, and fast detection remains a challenge. This paper addresses these real production needs by enhancing data
Externí odkaz:
http://arxiv.org/abs/2310.11379
Proper modelling of the gravitational fields of irregularly shaped asteroids and comets is an essential yet challenging part of any spacecraft visit and flyby to these bodies. Accurate density representations provide crucial information for proximity
Externí odkaz:
http://arxiv.org/abs/2306.01602
Recent advances in modeling density distributions, so-called neural density fields, can accurately describe the density distribution of celestial bodies without, e.g., requiring a shape model - properties of great advantage when designing trajectorie
Externí odkaz:
http://arxiv.org/abs/2305.19698
Onboard machine learning on the latest satellite hardware offers the potential for significant savings in communication and operational costs. We showcase the training of a machine learning model on a satellite constellation for scene classification
Externí odkaz:
http://arxiv.org/abs/2305.04059