Datasets:
metadata
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- machine-generated
languages:
- Ru
licenses:
- afl-3.0
multilinguality:
- monolingual
pretty_name: >-
The Pages of Early Soviet Performance (PESP) uses machine learning to generate
multiple datasets of early-Soviet illustrated periodicals related to the
performing arts. By using computer vision techniques and training a YOLO (You
Only Look Once) real-time object detection model, we are producing textual and
image data that will facilitate new avenues of research about Soviet culture
during the first decades after the October Revolution (1917-1932).
Our starting point is Princeton University Library's Digital PUL (DPUL) where
ten titles - totaling 526 issues and approximately 26,000 pages - of Soviet
performance journals have been digitized and can be freely viewed online.
Journals are a diverse and complex genre: taken together, this collection
contains hundreds of thousands of articles, poems, editorial commentary,
advertisements as well as images, illustrations and graphic art. Today,
researchers can browse the journals and view and download high-quality page
images on DPUL.
size_categories: []
source_datasets:
- original
task_categories:
- other
task_ids: []