Machine learning algorithms have increasingly become integral to gamma-ray spectroscopy, enabling automated feature extraction, classification and quantitative analysis from complex spectral data.
Monte Carlo simulations have become indispensable in gamma-ray spectrometry, enabling predictive modelling of photon interactions within complex source–detector geometries. By sampling large numbers ...