Timematrix for researchers
This webinar - aimed at academic researchers in data mining and data science - explores the potential of adapting automatically produced descriptions of paintings to the time period when they were created.
This webinar - aimed at academic researchers in data mining and data science - explores the potential of adapting automatically produced descriptions of paintings to the time period when they were created.
Day 1: Understanding the past through parallels with the present
Day 2. Technical implementation of the TimeMatrix
The Saint George on a Bike project aims to improve the quality and quantity of open metadata associated with imagery from European cultural heritage. It especially aims to address the challenge of providing Artificial Intelligence with insights into culture, symbols and traditions.
This webinar is aimed at academic researchers in data mining and data science who are interested in art and culture. It demonstrates results from the project and showcases the potential of adapting automatically produced descriptions of paintings to the time period when they were created. Participants are introduced to what we call the ‘time machine effect’, which consists of the objects of an image being transformed via deep learning methods to similar concepts that are more appropriate to another time period. The technical challenges and current solutions are discussed. At the end of the webinar, a demo shows the correction of anachronisms and class refinement examples.
This webinar took place over two days from 9 - 10 September 2020.
Maria Cristina Marinescu (CASE Department, Barcelona Supercomputing Center)
Joaquim More Lopez (CASE Department, Barcelona Supercomputing Center)
Artem Reshetnikov (CASE Department, Barcelona Supercomputing Center)
Albin Larsson (Europeana)