Is medieval distant viewing possible? : Extending and enriching annotation of legacy image collections using visual analytics.
Distant viewing approaches have typically used image datasets close to the contemporary image data used to train machine learning models. To work with images from other historical periods requires expert annotated data, and the quality of labels is crucial for the quality of results. Especially when...
| Publicado en: | Digital Scholarship in the Humanities Vol. 39; no. 2; pp. 638 - 657 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Oxford University Press / USA
Jun2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=177947264&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 177947264 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Jun2024 vid: 39 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 177947264 10.1093/llc/fqae020 ppf: 638 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P size: 2.5MB tig: atl: Is medieval distant viewing possible? : Extending and enriching annotation of legacy image collections using visual analytics. aug: au: Meinecke, Christofer Guéville, Estelle Wrisley, David Joseph Jänicke, Stefan affil: Image and Signal Processing Group, Leipzig University , Leipzig, Germany Medieval Studies, Yale University , New Haven, USA Arts & Humanities, New York University Abu Dhabi , Abu Dhabi, United Arab Emirates Department of Mathematics and Computer Science, University of Southern Denmark , Odense, Denmark su: Bible Visual analytics Supervised learning Medieval manuscripts Metadata Annotations sug: subj: Bible Visual analytics Supervised learning Medieval manuscripts Metadata Annotations keyword: Collections as Data Distant Viewing Latin Bibles Legacy Data Medieval Manuscripts Visual Analytics Visual Thinking Visualization in the Humanities Vocabulary Interoperability ab: Distant viewing approaches have typically used image datasets close to the contemporary image data used to train machine learning models. To work with images from other historical periods requires expert annotated data, and the quality of labels is crucial for the quality of results. Especially when working with cultural heritage collections that contain myriad uncertainties, annotating data, or re-annotating, legacy data is an arduous task. In this paper, we describe working with two pre-annotated sets of medieval manuscript images that exhibit conflicting and overlapping metadata. Since a manual reconciliation of the two legacy ontologies would be very expensive, we aim (1) to create a more uniform set of descriptive labels to serve as a "bridge" in the combined dataset, and (2) to establish a high-quality hierarchical classification that can be used as a valuable input for subsequent supervised machine learning. To achieve these goals, we developed visualization and interaction mechanisms, enabling medievalists to combine, regularize and extend the vocabulary used to describe these, and other cognate, image datasets. The visual interfaces provide experts an overview of relationships in the data going beyond the sum total of the metadata. Word and image embeddings as well as co-occurrences of labels across the datasets enable batch re-annotation of images, recommendation of label candidates, and support composing a hierarchical classification of labels. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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