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Authors: Jacob Murel and David Smith

Affiliation: Khoury College of Computer Sciences, Northeastern University, Boston, MA, U.S.A.

Keyword(s): Object Detection, YOLO, Historical Print, Handwriting, Digital Humanities.

Abstract: Early readers’ manuscript annotations in books have been analyzed by bibliographers for evidence about book history and reading practice. Since handwritten annotations are not uniformly distributed across or within books, however, even the compilers of censuses of all copies of a single edition have very seldom produced systematic information about these interventions in the lives of books. This paper analyzes the use of object detection models (ODMs) for detecting handwritten annotations on the pages of printed books. While computer vision developers have dealt widely with imbalanced datasets, none have addressed the effect of negative sample images on model accuracy. We therefore investigate the use of negative evidence—pages with no annotations—in training accurate models for this task. We also consider how different evaluation metrics are appropriate for different modes of bibliographic research. Finally, we create a labeled training dataset of handwritten annotations in early pr inted books and release it for evaluation purposes. (More)

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Paper citation in several formats:
Murel, J. and Smith, D. (2024). Detecting Manuscript Annotations in Historical Print: Negative Evidence and Evaluation Metrics. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 745-752. DOI: 10.5220/0012365600003654

@conference{icpram24,
author={Jacob Murel. and David Smith.},
title={Detecting Manuscript Annotations in Historical Print: Negative Evidence and Evaluation Metrics},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2024},
pages={745-752},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012365600003654},
isbn={978-989-758-684-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Detecting Manuscript Annotations in Historical Print: Negative Evidence and Evaluation Metrics
SN - 978-989-758-684-2
IS - 2184-4313
AU - Murel, J.
AU - Smith, D.
PY - 2024
SP - 745
EP - 752
DO - 10.5220/0012365600003654
PB - SciTePress

- Science and Technology Publications, Lda.
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