Seales, William
PI: Brent Seales
Digital Restoration
Recovering lost text from ancient or damaged manuscripts using non-invasive imaging and computation.
Computational Methods
We are using our Volume Cartographer library ((C++)) for the analysis of 3D volumetric CT data. Additionally, we are using ((Python)) and ((Tensorflow)) for further processing so that we can segment and classify writing surfaces and ink from a CT scan.
Project Members
Seth Parker (CS/Vis Center, UK CS Grad Student)
Stephen Parsons (CS/Vis Center)
Kyra Seevers
Daniel B Dopp, Dept of Marketing and Supply Chain
Ankan Bhattacharyya, Graduate, Added on LCC resources on 06/22/2022
Shunnan Chen, Added on LCC resources on 11/15/2022
Software Used:
Python
Tensorflow
GPUs
Insight Segmentation and Registration Toolkit (ITK)
Gemini Storage
Funding
Funding is provided through the Digital Restoration Initiative.
Publications (resulting from DLX usage):
None
Staff
Mami Hayashida (Research Computing Infrastructure, Digital Restoration Initiative) [mhaya2@uky.edu]
Center for Computational Sciences