Pattern Recognition for
Cultural
Heritage

The enormous amount of artifacts and information from the past is increasingly and rapidly digitized. However, the valuable information contained in these data is not easy to exploit, and some analysis is needed. On the other hand, the digital representations of real objects require some manipulation. Recent machine learning and pattern recognition algorithms allow the analysis and manipulation of the acquired data to exploit the contained information better and generate the best digital representation. This workshop presents recent advances in Pattern Recognition (PR) techniques for data analysis and representation in the cultural heritage field. Bringing together the work of many experts in this multidisciplinary subject to highlight these advances from a wide-angle perspective and stimulate new theoretical and applied research to better characterize this subject's state of the art.

(3rd Edition)

• Digital artifact capture, representation and manipulation
• Automatic annotation of tangible and intangible heritage
• Interactive software tools for cultural heritage applications
• Multimedia music classification and reconstruction
• Image processing, classification and retrieval
• Semantic segmentation
• Serious Game for Cultural Heritage
• Robotic applications
• Ontology Learning for cultural heritage domain
• Machine Learning for Cultural Heritage

Accepted papers will be included in the ICIAP 2023 Workshop Proceedings, which will be published by Springer in the Lecture Notes in Computer Science (LNCS). All papers to appear in the proceedings must follow the instructions set forth by Springer for the “preparation of proceedings papers published in the LNCS”.
For more details, see the submission page.