The study presents a review of research advancements in the field of gamma radiation
detection systems for emergency radiation monitoring, particularly two major sub-systems …

This paper presents a review of up-to-date advancements in detection algorithms employed
in radiation monitoring for generating radiation maps of ground contamination and tracking …

Anomalous radiation source detection in urban environments is challenging due to the
complex nature of background radiation. When a suspicious area is determined, a radiation …

The task of mixture proportion estimation (MPE) is to estimate the weight of a component
distribution in a mixture, given observations from both the component and mixture. Previous …

Unconventional scenarios with hazardous radioactive levels are expected as consequences
of accidents in the industrial sector of the nuclear energy production or following intentional …

This study introduces an explainable artificial intelligence (XAI) approach designed to
estimate background spectra in unknown spectral measurements. The approach combines …

An artificial neural network (ANN) that identifies radionuclides from low-count gamma
spectra of a NaI scintillator is proposed. The ANN was trained and tested using simulated …

This research aims at comparing the performance of different machine learning algorithms
used for NaI (TI) gamma-ray detector based radioisotope identification. Six machine learning …

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 …

Radioisotope identification presents challenges that can be effectively addressed through
pattern recognition and machine learning (ML) techniques. However, further investigation is …