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  • Image Analysis for Archival Discovery (Aida)

    Project Director(s):
    Elizabeth Lorang (see profile) , Leen-Kiat Soh
    Author(s):
    Elizabeth Lorang (see profile) , Leen-Kiat Soh
    Date:
    2016
    Group(s):
    American Literature, Archives, Data Rescue, Digital Humanists
    Subject(s):
    American literature, Archives--Study and teaching, Archaeology--Data processing, Digital humanities
    Item Type:
    White paper
    Institution:
    University of Nebraska, Board of Regents
    Tag(s):
    Digital Humanities Start-Up Grants, NEH Digital Humanities, NEH White papers, Archival studies, Digital archaeology, Digital archives
    Permanent URL:
    http://dx.doi.org/10.17613/M6665Z
    Abstract:
    Images created in the digitization of primary materials contain a wealth of machine-processable information for data mining and large-scale analysis, and this information should be leveraged both to connect researchers with the resources they need and to augment interpretation of human culture, as a complement to and extension of text-based approaches. The proposed project, "Image Analysis for Archival Discovery" (Aida), applies image processing and machine learning techniques from computer science to digitized materials to facilitate and promote archival discovery. Beginning with the automatic detection of poetic content in historic newspapers, this project will develop image processing as a methodology for humanities research and analysis. In doing so, it will advance work on two fronts: 1) it will contribute to the reevaluation of newspaper verse in American literary history; 2) it will assess the application of image analysis as a method for discovery in archival collections.
    Notes:
    The development of a prototype tool that would allow scholars and students to apply image processing and machine learning techniques to identify specific visual elements within digitized collections. The project would start with an attempt to identify poetry found in the Chronicling America collection of historic newspapers.
    Metadata:
    xml
    Status:
    Published
    Last Updated:
    6 years ago
    License:
    Attribution-NonCommercial

    Downloads

    Item Name: pdf hd-51897-14.pdf
      Download View in browser
    Activity: Downloads: 209

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