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Full-Text Articles in Arts and Humanities

Application Of The Image Analysis For Archival Discovery Team’S First- Generation Methods And Software To The Burney Collection Of British Newspapers, Elizabeth Lorang, Leen-Kiat Soh, Chulwoo Pack, Yi Liu, Delaram Rahimighazikalayeh, John O'Brien May 2019

Application Of The Image Analysis For Archival Discovery Team’S First- Generation Methods And Software To The Burney Collection Of British Newspapers, Elizabeth Lorang, Leen-Kiat Soh, Chulwoo Pack, Yi Liu, Delaram Rahimighazikalayeh, John O'Brien

CDRH Grant Reports

The current study, “Application of the Image Analysis for Archival Discovery Team’s First- Generation Methods and Software to the Burney Collection of British Newspapers,” is the first test of our approaches—methods and software—to a different newspaper corpus, specifically the 17th and 18 Century Burney Newspapers Collection. This study stands as the first complete attempt at applying Aida’s software and methods to non-Chronicling America newspapers, as a step toward understanding the potential of our approaches across digitized historic newspapers. In taking this step, our goals were (1) to test how well the software and a classifier model developed on Chronicling America …


Interim Performance Report, Lg‐71‐16‐0152‐16, Extending Intelligent Computational Image Analysis For Archival Discovery, March 2019, Elizabeth Lorang, Leen-Kiat Soh, John O'Brien Mar 2019

Interim Performance Report, Lg‐71‐16‐0152‐16, Extending Intelligent Computational Image Analysis For Archival Discovery, March 2019, Elizabeth Lorang, Leen-Kiat Soh, John O'Brien

CDRH Grant Reports

The primary goal of "Extending Intelligent Computational Image Analysis for Archival Discovery" is to investigate the use of image analysis as a methodology for content identification, description, and information retrieval in digital libraries and other digitized collections. Building on work started under a National Endowment for the Humanities' Office of Digital Humanities Start-up Grant, our IMLS project seeks to 1) analyze and verify our previously developed image analysis approach and extend it so that it is newspaper agnostic, type agnostic, and language agnostic; 2) scale and revise the intelligent image analysis approach and determine the ideal balance between precision and …


White Paper, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh Oct 2016

White Paper, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh

CDRH Grant Reports

With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aida) team set out to further develop image analysis as a methodology for the identification and retrieval of items of relevance within digitized collections of historic materials.1 Specifically, we sought to identify poetic content within historic newspapers, using Chronicling America's newspapers (http://chroniclingamerica.loc.gov/) as our test case. The project activities we undertook—both those completed and those in process—support this goal and align well with the activities proposed in our original funding application and as approved by NEH. To achieve our goal of creating an image processing-based system …


Final Report, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh Oct 2016

Final Report, Hd-51897-14, Image Analysis For Archival Discovery (Aida), October 2016, Elizabeth M. Lorang, Leen-Kiat Soh

CDRH Grant Reports

With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aida) team set out to further develop image analysis as a methodology for the identification and retrieval of items of relevance within digitized collections of historic materials. Specifically, we sought to identify poetic content within historic newspapers, using Chronicling America's newspapers (http://chroniclingamerica.loc.gov/) as our test case. The project activities we undertook—both those completed and those in process—support this goal and align well with the activities proposed in our original funding application and as approved by NEH. To achieve our goal of creating an image processing-based system …


Developing An Image-Based Classifier For Detecting Poetic Content In Historic Newspaper Collections, Elizabeth M. Lorang, Leen-Kiat Soh, Maanas Varma Datla, Spencer Kulwicki Mar 2015

Developing An Image-Based Classifier For Detecting Poetic Content In Historic Newspaper Collections, Elizabeth M. Lorang, Leen-Kiat Soh, Maanas Varma Datla, Spencer Kulwicki

UNL Libraries: Faculty Publications

"Developing an Image-Based Classifier for Detecting Poetic Content in Historic Newspaper Collections" details and analyzes the first stage of work of the Image Analysis for Archival Discovery project team. Our team is is investigating the use of image analysis to identify poetic content in historic newspapers. The project seeks both to augment the study of literary history by drawing attention to the magnitude of poetry published in newspapers and by making the poetry more readily available for study, as well as to advance work on the use of digital images in facilitating discovery in digital libraries and other digitized collections. …


The Collected Poems Of Gavin Turnbull Online, Patrick G. Scott, John Knox, Rachel Mann Jan 2015

The Collected Poems Of Gavin Turnbull Online, Patrick G. Scott, John Knox, Rachel Mann

Digital Projects

The Collected Poems of Gavin Turnbull contains 89 individual poems and songs, organized according to the date of their first publication. The poems are grouped into one of four sections, following the sequence of the books, manuscript, or periodicals in which they are first found. Turnbull's two prose prefaces (1788, 1794) and his short play The Recruit (also 1794) are included, but placed last, after the poems, as Appendices.

A list of the individual poems and songs in each section and links to the texts are available in the gray drop-down menu on the left-hand side of the screen. With …