We describe an intelligent image analysis approach to automatically detect poems in digitally archived historic newspapers. Our application, Image Analysis for Archival Discovery, or Aida, integrates computer vision to capture visual cues based on visual structures of poetic works—instead of the meaning or content—and machine learning to train an artificial neural network to determine whether an image has poetic text. We have tested our application on almost 17,000 image snippets and obtained promising accuracies, precision, and recall. The application is currently being deployed at two institutions for digital library and literary research
International audienceThis paper aims to communicate an ongoing research project conducted at Columb...
Understanding the contents of handwritten texts from document images has long been a traditional fie...
Archival institutions and program worldwide work to ensure that the records of governments, organiza...
Developing an Image-Based Classifier for Detecting Poetic Content in Historic Newspaper Collections ...
With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aid...
In the second six months of work on Image Analysis for Archival Discovery, the project team has co...
In the third six months of work on Image Analysis for Archival Discovery, the project team has mad...
This presentation situates the work of the Aida team broadly as well as hinges this work on some ver...
Image snippets and analysis files for the Aida team\u27s case study of poetic content in digitized n...
Presentation given at the Workshop - Twin Talks: Understanding Collaboration in DH at DHN 2019, see ...
Digital humanities research has focused primarily on the analysis of texts. This emphasis stems from...
Marriott Library received funding to explore the feasibility of using image analysis to generate des...
In 1962, Dutch celebrity Ria Kuyken was attacked by a circus bear. Cees de Boer captured this moment...
This presentation summarized and presented preliminary results from the first weeks of work conducte...
Numerous valuable historic and cultural sources - a major part of our cultural heritage - are curren...
International audienceThis paper aims to communicate an ongoing research project conducted at Columb...
Understanding the contents of handwritten texts from document images has long been a traditional fie...
Archival institutions and program worldwide work to ensure that the records of governments, organiza...
Developing an Image-Based Classifier for Detecting Poetic Content in Historic Newspaper Collections ...
With its Office of Digital Humanities Start-up Grant, the Image Analysis for Archival Discovery (Aid...
In the second six months of work on Image Analysis for Archival Discovery, the project team has co...
In the third six months of work on Image Analysis for Archival Discovery, the project team has mad...
This presentation situates the work of the Aida team broadly as well as hinges this work on some ver...
Image snippets and analysis files for the Aida team\u27s case study of poetic content in digitized n...
Presentation given at the Workshop - Twin Talks: Understanding Collaboration in DH at DHN 2019, see ...
Digital humanities research has focused primarily on the analysis of texts. This emphasis stems from...
Marriott Library received funding to explore the feasibility of using image analysis to generate des...
In 1962, Dutch celebrity Ria Kuyken was attacked by a circus bear. Cees de Boer captured this moment...
This presentation summarized and presented preliminary results from the first weeks of work conducte...
Numerous valuable historic and cultural sources - a major part of our cultural heritage - are curren...
International audienceThis paper aims to communicate an ongoing research project conducted at Columb...
Understanding the contents of handwritten texts from document images has long been a traditional fie...
Archival institutions and program worldwide work to ensure that the records of governments, organiza...