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Found 6 papers, 3 papers with code
The "Collections as ML Data" Checklist for Machine Learning & Cultural Heritage
By surveying existing projects, including my own project, Newspaper Navigator, I justify the "Collections as ML Data" checklist and demonstrate how the formulated guiding questions can be employed and operationalized.
Grappling with the Scale of Born-Digital Government Publications: Toward Pipelines for Processing and Searching Millions of PDFs
This paper utilizes a Library of Congress dataset of 1, 000 government PDFs in order to offer initial approaches for searching and analyzing these PDFs at scale.
Navigating the Mise-en-Page: Interpretive Machine Learning Approaches to the Visual Layouts of Multi-Ethnic Periodicals
This paper presents a computational method of analysis that draws from machine learning, library science, and literary studies to map the visual layouts of multi-ethnic newspapers from the late 19th and early 20th century United States.
LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis
Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks.
The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America
We report the results of running the pipeline on 16. 3 million pages from the Chronicling America corpus and describe the resulting Newspaper Navigator dataset, the largest dataset of extracted visual content from historic newspapers ever produced.
LIMEADE: From AI Explanations to Advice Taking
We show our method improves accuracy compared to a rigorous baseline on the image classification domains.
