Creating a quantitative overview over the early Iron Age heritage of the Eurasian steppes is
a difficult task due to the vastness of the ecological zone and the often problematic access …

In computer vision, convolutional neural networks (CNNs) obtain extremely striking
recognition performance. However, in many CNNs there exists a great deal of parameter …

The ARCADIA project aims at using pattern recognition and machine learning to promote a
systematic analysis of the large corpus of archaeological pottery fragments excavated in …

An in-depth description of the state-of-the-art of 3D shape analysis techniques and their
applications This book discusses the different topics that come under the title of" 3D shape …

In this paper, we addressed the problem faced by archaeologists in associating relief-printed
decorations on ceramic objects discovered during excavations carried out with the same …

There is an active trade in human remains facilitated by social media sites. In this paper we
ask: can machine learning detect visual signals in photographs indicating that the human …

The separation of discrete fossiliferous levels within an archaeological or paleontological
site with no clear stratigraphic horizons has historically been carried out using qualitative …

Archaeologists are accustomed to constructing narratives cast within periods frequently
defined by the rise and ultimate replacement of distinctive technologies. Contemporary …

Although existing research on classification of Chinese paintings is limited to consideration
of the relationship between paintings and labels, we propose a convolutional neural network …

La reconnaissance d'objet 3D est un sous-domaine très important de la vision par
ordinateur et du multimédia. De nombreuses organisations ont d'importantes collections …