Convolutional Neural Networks

Detection of Buried Landmines using a Convolutional Autoencoder trained on Simulated prompt Gamma Spectra

The detection of buried landmines remains a persistent challenge in security and humanitarian demining. In this work, we present an indirect detection methodology based on the analysis of prompt gamma-ray emissions induced by 14 MeV neutron …

Deep learning on simulated gamma spectra for explosives detection using a NaI detector

The detection of explosives and contraband materials using neutron activation analysis (NAA) is a critical component of modern security systems. This study investigates the feasibility of identifying explosive materials using a simple sodium iodide …

Simulated near-field radioactive source localization in 3D with Coded Aperture and Convolutional Neural Networks

Coded Aperture γ-cameras have been extensively used in applications ranging from astrophysics to nuclear medicine for imaging radioactive source distributions. These devices allow the identification of the direction of γ-emitters by analyzing the …