Morphological Classification of Galaxies in S-PLUS using an Ensemble of Convolutional Networks

no code implementations • 5 Jul 2021 • N. M. Cardoso, G. B. O. Schwarz, L. O. Dias, C. R. Bom, L. Sodré Jr., C. Mendes de Oliveira

In terms of classification, we achieved, with the Ensemble, an accuracy of $\approx 99 \%$ in the test sample (using pre-trained networks).

Classification

Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan"

no code implementations • 5 Nov 2019 • J. Amundson, J. Annis, C. Avestruz, D. Bowring, J. Caldeira, G. Cerati, C. Chang, S. Dodelson, D. Elvira, A. Farahi, K. Genser, L. Gray, O. Gutsche, P. Harris, J. Kinney, J. B. Kowalkowski, R. Kutschke, S. Mrenna, B. Nord, A. Para, K. Pedro, G. N. Perdue, A. Scheinker, P. Spentzouris, J. St. John, N. Tran, S. Trivedi, L. Trouille, W. L. K. Wu, C. R. Bom

Thus far the US has been a leader in AI technologies, and we believe as a national Laboratory it is crucial to help maintain and extend this leadership.

A Neural Network Gravitational Arc Finder based on the Mediatrix filamentation Method

no code implementations • 15 Jul 2016 • C. R. Bom, M. Makler, M. P. Albuquerque, C. H. Brandt

In this work we introduce a new arc finder based on pattern recognition, which uses a set of morphological measurements derived from the Mediatrix Filamentation Method as entries to an Artificial Neural Network (ANN).

Cosmology and Nongalactic Astrophysics