Topics of interest include, but are not limited to:

• Machine learning and data science for cultural heritage multimedia data

• Discrete geometry techniques for pattern recognition in cultural heritage images

• Combinatorial pattern matching and discovery in ancient images

• Graph-based methods for cultural heritage multimedia data

• Signal processing in the cultural heritage

• Intelligent systems for art restoration

• Augmented and virtual reality systems

• 3D reconstruction and model processing

• 3D modelling and simulation of cultural heritage items

• Classification or clustering of acoustic data from the cultural heritage

• Image processing, texture and shape analysis in historical data

• Computer vision for pattern extraction from cultural heritage images

• Remote sensing for cultural heritage preservation

• Data Mining for historical language recognition

• Image similarity and segmentation for the cultural heritage

• Deep learning applied to cultural heritage multimedia data

• Nature-inspired algorithms for historical multimedia data

• Natural Language Processing in the cultural heritage

• Knowledge representation and ontologies for ancient multimedia data

• Historical document processing and classification

• Speech, audio and music recognition and analysis from historical archives

• Archiving and searching methods for cultural heritage multimedia data

• Information retrieval in cultural heritage multimedia collections

• Discrimination and recognition of ancient languages and dialects

• Feature selection and extraction from cultural heritage multimedia data

• Ensemble methods for visual understanding of cultural heritage

• Industrial products, projects, prototypes and artefacts for cultural heritage preservation

• Explainable AI for the recognition of ancient multimedia data