The University of North Texas (UNT) Libraries in partnership with the University of Illinois at Chicago were awarded a National Leadership Grant (IMLS:LG-71-17-0202-17) from the Institute of Museum and Library Services (IMLS) to research the efficacy of using machine-learning algorithms to identify and extract content-rich publications contained in web archives. With the increase of institutions that are collection web-published content into web archives, there has been growing interest in mining these web archives to extract publications or documents that align with existing collections or collection development policies. These identified publications could then be integrated into existing digital library collections where they would become first-order digital objects instead of content accessible only to discovery by traversing the web archive or though a well crafted full text search. This project is focusing on the first piece of this workflow, to identify the publications that exist and separate them from content that does not align with existing collections. To operationalize this research, the project is focusing on three primary use cases, including: extracting scholarly publications for an institutional repository from a university domain's web archive (unt.edu

The new Open Images dataset gives us everything we need to train computer vision models, and just happens to be perfect for a demo! Tensorflow's Object Detection API and its ability to handle large volumes of data make it a perfect choice, so let's jump right in… Open Images is a dataset created by Google that has a significant number of freely licensed annotated images. Initially it contained only classification annotations, or in simpler terms it had labels that described what, but not where. After a major version update to 2.0, more annotations were added – of particular importance were the introduction of object detection annotations. These new annotations not only described what was in a picture, but where it was located, by defining the bounding box (bbox) coordinates for specific objects in an image.