output
20032024
most citedThe Gaia mission

7.1k citations

Showing 2020Show all

10 papers · 1 filter

astro-ph.GA202014 cited

S2D2: Small-scale Significant substructure DBSCAN Detection I. NESTs detection in 2D star-forming regions

Marta González, Isabelle Joncour, Anne S. M. Buckner +13

The spatial and dynamical structure of star-forming regions can help provide insights on stellar formation patterns. The amount of data from current and upcoming surveys calls for…

astro-ph.SR20209 cited

Wide binaries in Planetary Nebulae with Gaia DR2

I. González-Santamaría, M. Manteiga, A. Manchado +3

Gaia Data Release 2 (DR2) was used to select a sample of 211 central stars of planetary nebulae (CSPNe) with good quality astrometric measurements, that we refer to as GAPN, Golden…

nucl-ex202017 cited

Manifestation of the Berry phase in the atomic nucleus Pb

J. J. Valiente-Dobón, A. Gottardo, G. Benzoni +57

The neutron-rich Pb isotope was produced in the fragmentation of a primary 1 GeV U beam, separated in FRS in mass and atomic number, and then implanted for isom…

eess.AS20201 cited

Alzheimer's Dementia Detection from Audio and Text Modalities

Edward L. Campbell, Laura Docío-Fernández, Javier Jiménez Raboso +1

Automatic detection of Alzheimer's dementia by speech processing is enhanced when features of both the acoustic waveform and the content are extracted. Audio and text transcription…

cs.NI20202 cited

Leveraging Energy Saving Capabilities of Current EEE Interfaces via Pre-Coalescing

Miguel Rodríguez Pérez, Sergio Herrería Alonso, Raúl F. Rodríguez Rubio +1

The low power idle mode implemented by Energy Efficient Ethernet (EEE) allows network interfaces to save up to 90% of their nominal energy consumption when idling. There is an ampl…

cs.CV202017 cited

FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformations

Manuel Rey-Area, Emilio Guirado, Siham Tabik +1

It is widely known that very small datasets produce overfitting in Deep Neural Networks (DNNs), i.e., the network becomes highly biased to the data it has been trained on. This iss…