Saint George on a Bike (SGoaB) aims to improve the quality and quantity of open metadata associated with European Cultural Heritage (CH) imagery. To achieve that goal SGoaB addresses two challenges: (i) to transcribe insights about culture, symbols and centuries of evolving iconographic traditions in a knowledge representation accessible to machine learning and artificial intelligence, (ii) to expand conventional machine learning approaches, centered on image recognition, with the ability to decipher the complex pictorial language that characterises iconographic symbols and sacred imagery.
Build on neural network based image recognition procedures to include complex cultural knowledge representations, in order to generate rich metadata.
Harnesses semantic web and information retrieval capabilities to identify and create relevant contexts for images, which reflect their cultural heritage
Use enriched metadata in search services applied to CH objects.
Provide scalable functionality via High-Performance Computing (HPC)
