Toward the Standardisation of Annotation Data for Patrimonial Images: A Case of Layout Detection for Art Magazines.

This article addresses the epistemological and methodological issues of computer vision applied to art historical corpora by highlighting the challenges of the use of heterogeneous and diverse formats and tools for annotation. Authors underline the importance of working towards the standardization o...

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Published in:Digital Humanities in the Nordic & Baltic Countries Publications (DHNB Publications) Vol. 7; no. 3; pp. 1 - 17
Main Authors: Truc, Alice, Maronet, Léa
Format: Article
Published: University of Oslo 2025
Subjects:
Online Access:View this record in EBSCOhost
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        10.5617/dhnbpub.12268
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        atl: Toward the Standardisation of Annotation Data for Patrimonial Images: A Case of Layout Detection for Art Magazines.
      aug:
        au:
          Truc, Alice
          Maronet, Léa
        affil:
          Université de Montréal
          Université Rennes 2
          Centre National de la Recherche Scientifique (CNRS)
          École Pratique des Hautes Études (EPHE)
      su:
        Standardization
        Annotations
        Object recognition (Computer vision)
        Photography archives
        Computer vision
        Magazine design
        Pattern perception
      sug:
        subj:
          Standardization
          Annotations
          Object recognition (Computer vision)
          Photography archives
          Computer vision
          Magazine design
          Pattern perception
      keyword:
        Annotation
        Ground truth
        Patrimonial images
        Segmentation
        Standards
      ab: This article addresses the epistemological and methodological issues of computer vision applied to art historical corpora by highlighting the challenges of the use of heterogeneous and diverse formats and tools for annotation. Authors underline the importance of working towards the standardization of patrimonial image annotation by addressing our need for interoperable and reproducible data, in order to fine-tune models for automatic object recognition applied to patrimonial images. The authors advocate that the sharing of annotation data should be assumed by collaborative endeavors among cultural institutions.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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