Radionuclide identification is an important part of the nuclear material identification system.
The development of artificial intelligence and machine learning has made nuclide …

This study proposes a novel feature extraction approach for radionuclide identification to
increase the precision of identification of the gamma-ray energy spectrum set. For easier …

Rapid nuclide identification is crucial in improving the performance of radioactivity
monitoring. Rapid measurement of considerable fluctuation and noise in gamma-ray spectra …

Objective Rapid and reliable radionuclide identification can enable rapid monitoring and
early warning of radioactive sources, which is essential for safeguarding people from the …

Traditional radionuclide identification algorithms are based on gamma-ray spectrum
analysis. A novel radionuclide identification method was proposed in this work and it was …

As a rapid and automatic method, multiple radionuclide identification using deep learning
has drawn wide interest from researchers in the field of nuclear safety and nuclear security …

Nuclide identification technology plays a critical role in various fields such as nuclear
energy, medicine, environmental monitoring, and defense. However, traditional nuclide …

Rapid and precise radioisotope identification in the scene of nuclear detection and nuclear
security incidents is one of the challenging issues for the prompt response to the detection …

According to the international nuclear safeguards and inspection system, it is one of the
most important aspects to detect and verify the plutonium contained in samples instantly …

We have proposed a machine learning model for efficient gamma-ray spectrometry for
environmental recovery from the Fukushima Daiichi Power Plant Accident. In the present …