Abstract
This study focuses on the deep learning methods for face recognition in order to spot society patterns from historical databases. The results can enrich historical narratives by quantifying visual cues that are often overlooked in traditional archival research. Scanned photographs from the early 20th century have been used to perform recognition of the basic facial attributes – gender, age and emotion.