2024/03/01 by Finnish Heritage Agency, Niko Anttiroiko · 1 voice · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #Advanced Neural Network Applications
paper · pdf · doi:10.11141/ia.66.6
openalex publication_date 2024/03/01 · openalex created_date 2024/03/20 · openalex updated_date 2026/07/31
Recent advances in machine learning and computer vision techniques have brought (semi-)automatic feature detection within reach of an increasing number of archaeologists and archaeological institutions, including those in Finland. These techniques improve our ability to detect and gather information on archaeological cultural heritage over vast areas in a highly efficient manner. However, the widespread adoption of such methods can also pose significant challenges for archaeological cultural heritage management, especially in relation to certain types of near-ubiquitous archaeological remains from the 17th-20th centuries.