What Should We Do With These? Challenges related to (semi-)automatically detected sites and features. A note

Bibliographic Data

ID21147722
AuthorsFinnish Heritage Agency (Finnish Transport Agency, corresponding author), Niko Anttiroiko (Finnish Transport Agency)
Year2024
Issue66
Publication date2024-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternet Archaeology (JOURNAL)
Journal identifiersISSN: 1363-5387 • E-ISSN: 1363-5387
PublisherCouncil for British Archaeology (PUBLISHER • GB)
DOI10.11141/ia.66.6
OpenAlexW4392956410
LanguageEN
Citations received1
References cited7

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

Advanced Neural Network Applications · Anomaly Detection Techniques and Applications · Computer Science · Domain Adaptation and Few-Shot Learning · History

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