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*Centering The Human Expert: Experiments in Computer Vision Infrastructure for Digital Collection Management

Home / Project Briefing Pages / CNI Spring 2021 Project Briefing / *Centering The Human Expert: Experiments in Computer Vision Infrastructure for Digital Collection Management

March 8, 2021

Matthew Lincoln
Collections Information Architect
Carnegie Mellon University

Julia Corrin
University Archivist
Carnegie Mellon University

Emily Davis
Archivist
Carnegie Mellon University

We will report on a computer vision (CV) and GUI experiment at Carnegie Mellon University Libraries to incorporate visual similarity search to help archivists and metadata specialists search, de-duplicate, and describe a large institutional photo archive. Rather than trying to replace the archivist by creating an image classifier, we aimed to make a flexible, search-based technological aid that centered the human decision-maker. The main goal of this prototype was to test what combination of system architecture and user interfaces would be most useful for a production-ready CV infrastructure for managing visual digital collections, and begin to think about how it could impact wider workflows for describing, linking, and publishing our collections. After describing the challenges presented by this particular collection and the specific experimental tasks and results we did, we will discuss the immediate implications for archival organization, UI design, and CV research, particularly the need for models fine-tuned to historical, non-born-digital photographs, and the risks of reinforcing systemic racial and gender bias when using pretrained CV models.

https://doi.org/10.1184/R1/12791807

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Filed Under: CNI Spring 2021 Project Briefing, Digital Curation, Emerging Technologies, Project Briefing Pages
Tagged With: cni2021spring, Project Briefings & Plenary Sessions, Videos

Last updated:  Thursday, October 7th, 2021

 

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