Conveners
Session 1: Data Science and Astrophysics - use case examples
- Chair: Vito Conforti (Istituto Nazionale di Astrofisica (INAF))
Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of millions of images and deriving scientific results from them will require quantifying the efficiency and bias of any search method. I present a description...
The availability of data to astronomers is increasing exponentially every day and a strong synergy between machine learning (ML) algorithms, Big Data and proper computational environment is mandatory. In this context, Cloud Platforms could make a difference allowing to exploit the proper tools of the Data Science while offering the right computational environment for Machine Learning...
This work presents a Deep Neural Network (DNN) approach for the detection of GRBs notified by external instruments in the AGILE-GRID energy range, between 100 MeV and 10 GeV, where time and position of the GRB is known in advance. Taking into account the complex observation pattern of AGILE, we developed a Convolutional Neural Network (CNN), a class of DNN mainly used for image classification,...
