14 citations · 15 across the 2 of their papers we have counts for
5 papers · 1 filter
The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves
C. Donoso-Oliva, G. Cabrera-Vives, P. Protopapas +2
In the new era of very large telescopes, where data is crucial to expand scientific knowledge, we have witnessed many deep learning applications for the automatic classification of…
The Automatic Learning for the Rapid Classification of Events (ALeRCE) Alert Broker
F. Förster, G. Cabrera-Vives, E. Castillo-Navarrete +37
We introduce the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self--consistent classifica…
Alert Classification for the ALeRCE Broker System: The Light Curve Classifier
P. Sánchez-Sáez, I. Reyes, C. Valenzuela +23
We present the first version of the ALeRCE (Automatic Learning for the Rapid Classification of Events) broker light curve classifier. ALeRCE is currently processing the Zwicky Tran…
Nowcasting the turbulence at the Paranal Observatory
J. Milli, R. Gonzalez, P. R. Fluxa +13
At Paranal Observatory, the least predictable parameter affecting the short-term scheduling of astronomical observations is the optical turbulence, especially the seeing, coherence…
Deep Learning for Image Sequence Classification of Astronomical Events
Rodrigo Carrasco-Davis, Guillermo Cabrera-Vives, Francisco Förster +6
We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This ap…