Related papers: Crossmatching variable objects with the Gaia data
Visual object tracking acts as a pivotal component in various emerging video applications. Despite the numerous developments in visual tracking, existing deep trackers are still likely to fail when tracking against objects with dramatic…
Gaia is an ambitious space observatory devoted to obtain the largest and most precise astrometric catalogue of astronomical objects from our Galaxy and beyond. On-board processing and transmission of the huge amount of data generated by the…
We investigate the capabilities of the ESA Gaia mission for detecting and character- izing short timescale variability, from tens of seconds to a dozen hours. We assess the efficiency of the variogram analysis, for both detecting short…
Each year, thousands of people learn new visual categorization tasks -- radiologists learn to recognize tumors, birdwatchers learn to distinguish similar species, and crowd workers learn how to annotate valuable data for applications like…
There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic)…
Current gait recognition research mainly focuses on identifying pedestrians captured by the same type of sensor, neglecting the fact that individuals may be captured by different sensors in order to adapt to various environments. A more…
Classification of Visual Object Classes represents one of the most elaborated areas of interest in Computer Vision. It is always challenging to get one specific detector, descriptor or classifier that provides the expected object…
A key step in the Bayesian workflow for model building is the graphical assessment of model predictions, whether these are drawn from the prior or posterior predictive distribution. The goal of these assessments is to identify whether the…
Identifying and removing binary stars from stellar samples is a crucial but complicated task. Regardless of how carefully a sample is selected, some binaries will remain and complicate interpretation of results, especially via flux…
Visual search is an essential part of almost any everyday human goal-directed interaction with the environment. Nowadays, several algorithms are able to predict gaze positions during simple observation, but few models attempt to simulate…
The ESA global astrometry space mission Gaia has been monitoring the position of a billion stars since 2014. The analysis of such a massive dataset is challenging in terms of the data processing involved. In particular, the blind detection…
We present a method to identify likely visual binaries in Gaia eDR3 that does not rely on parallax or proper motion. This method utilizes the various PSF sizes of 2MASS/Gaia, where at $<2.5$" two stars may be unresolved in 2MASS but…
The publications of Gaia DR2 and DR3 have brought major improvements in stellar astrometry and photometry, particularly regarding the description of the white dwarf sequence. Notably, Gaia DR2 enabled the detection of variability in white…
ESA recently called for new "Science Ideas" to be investigated in terms of feasibility and technological developments -- for technologies not yet sufficiently mature. These ideas may in the future become candidates for M or L class missions…
The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning…
Similarity choice data occur when humans make choices among alternatives based on their similarity to a target, e.g., in the context of information retrieval and in embedding learning settings. Classical metric-based models of similarity…
Before the publication of the Gaia Catalogue, the contents of the first data release have undergone multiple dedicated validation tests. These tests aim at analysing in-depth the Catalogue content to detect anomalies, individual problems in…
When dealing with multi-class classification problems, it is common practice to build a model consisting of a series of binary classifiers using a learning paradigm which dictates how the classifiers are built and combined to discriminate…
We present a general probabilistic formalism for cross-identifying astronomical point sources in multiple observations. Our Bayesian approach, symmetric in all observations, is the foundation of a unified framework for object matching,…
Context. The Gaia third Data Release (DR3) presents the first catalogue of full-sky variable Young Stellar Object (YSO) candidates observed by the Gaia space telescope during the initial 34 months of science operations. Aims. Numerous types…