Ceramics analysis, classification, and reconstruction are essential to know an
archaeological site's history, economy, and art. Traditional methods used by the …

Artificial intelligence (AI) techniques have been increasingly applied in assisting various
cultural heritage (CH)-related tasks. The aim of this study is to examine the research trends …

Image recognition and classification in the domain of cultural heritage is a complex task that
usually requires good image quality and a large dataset. Small dataset is an apparent …

Deep learning models have gained widespread acceptance in recent decades for their
ability to recognize human activities. In terms of automated feature extraction capability and …

Code and data sharing are crucial practices to advance toward sustainable archaeology.
This article explores the performance of supervised machine learning classification methods …

Smartphone sensor-based Human Activity Recognition (HAR) is a significant facilitator for
many real-world applications such as smart homes, personal healthcare, and illness …

Rapid progress in digitisation and computer techniques have enabled noteworthy new
pottery analysis applications in recent decades. We focus on analytical techniques directed …

In this paper we propose an artificial intelligence imaging solution to support archaeologists
in the classification task of Roman commonware potsherds. Usually, each potsherd is …

Machine learning and deep neural network developments have evolved image
classification. This study offers a new neural network design with segmentation and …

Considering the substantial inaccuracies inherent in the traditional manual identification of
ceramic categories and the issues associated with analyzing ceramics based on chemical or …