Speakers
Description
King Augeas of Elis possessed the largest herd of cattle, goats and horses in all of Greece. For 30 years he did nothing to prevent his animals from polluting the floors of his stables with a mountain of dung. It took the strenght and ingenuity of Hercules to clean up the mess.
For 30 years museums, libraries and archives have put in an enormous effort to digitize their image collections. In most cases they used local vocabulary systems to provide subject metadata to describe image content. As a result the AI models that might help us with the analysis of iconography have to be trained on messy metadata.
Unfortunately we cannot call Hercules to clean up our stable. We can, however, use an accepted standard for iconography - ICONCLASS - to produce better organized metadata to boost the quality of AI models.
The ICONCLASS platform we are presently developing will facilitate collaboration, allowing groups of researchers to actually work together on shared datasets of images. The improved metadata will then be used to re-train our AI model so with every loop the performance of the AI agent we are developing for image analysis should get better.
In April we shall demonstrate where we are and invite others to test what we have made and collaborate with us to improve it further.