  In this paper, we report on our efforts for using Deep Learning for
classifying artifacts and their features in digital visuals as a part of the
Neoclassica framework. It was conceived to provide scholars with new methods
for analyzing and classifying artifacts and aesthetic forms from the era of
Classicism. The framework accommodates both traditional knowledge
representation as a formal ontology and data-driven knowledge discovery, where
cultural patterns will be identified by means of algorithms in statistical
analysis and machine learning. We created a Deep Learning approach trained on
photographs to classify the objects inside these photographs. In a next step,
we will apply a different Deep Learning approach. It is capable of locating
multiple objects inside an image and classifying them with a high accuracy.
