Hyperspectral imaging (HSI) has become widely used in cultural heritage (CH). This very
efficient method for artwork analysis is connected with the generation of large amounts of …

In recent years, machine learning (ML) has gained significant importance in the field of
cultural heritage research. Its advanced data analysis techniques have become a crucial …

Recent advancements of noninvasive imaging techniques applied for the study and
conservation of paintings have driven a rapid development of cutting-edge computational …

EDXRF spectrometry is a well-established and often-used analytical technique in examining
materials from which cultural heritage objects are made. The analytical results are …

This update covers the literature published between approximately June 2022 and April
2023 and is the latest part of a series of annual reviews. It is designed to provide the reader …

Generating chemical element maps of paintings from X-ray fluorescence (XRF) data is a
very valuable tool for the scientific community of conservators and art historians. Hand-held …

Macroscopic X-ray fluorescence (MA-XRF) datasets are analyzed using Artificial Neural
Networks. Specifically, Convolutional Neural Networks (CNNs) are trained by coupling the …

X-ray fluorescence (XRF) analysis of art objects has rapidly gained popularity since the late
2000s due to its increased accessibility to scientists. This introduced an imaging component …

Attribution and authentication of paintings are difficult tasks, often based on human
expertise. In this work, we present SpectrumArt: a new dataset of multispectral (13 channels) …

This work comprehensively reviews artificial intelligence (AI) methods for macroscopic X-ray
fluorescence (MA-XRF) data analysis of a religious panel painting (icon). ΜΑ-XRF is a …