A Digital Image Library: Making it possible with Facial Recognition




Prud'homme, Max
Peta, Lokesh

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Texas Digital Library


Ensuring the discovery and preservation of digital archival assets is an important aspect of digital curation work at the Oklahoma State University Library. In the fall of 2023, the university archives resumed their machine learning work after conducting a successful pilot project that explored the use of facial recognition techniques to curate a high-value archival collection. With support from Library Administration, the digital archives are moving forward with the development of a dynamic search engine, using machine learning, to improve the predictability and performance for searching thousands of digital assets. To achieve this, the team is constructing a model that is easily trainable and an interactive application to search images more efficiently. With consideration to scalability and sustainability, the facial recognition technology used in the pilot project is being extended to a larger and more diverse dataset of face images. The presenters propose to showcase the project flow, context, planning, design and architecture in a demonstration/tutorial-like presentation. They will address challenges and initial feedback, with a particular focus on scalability, sustainability, as well as ethical issues associated with facial recognition technology.


TCDL 2023 Session 2F, Wednesday, 5/17/2023, 11:00 am to 12:00 pm | Moderated by Sylvia Jones, Southern Methodist University | Demonstration | Collections, Metadata, & Digital Preservation