Izboljšave muzejskega in arhivskega digitaliziranega slikovnega gradiva s postopki, ki temeljijo na umetni inteligenci oz. strojnem učenju - Hribar, Luka (Moderna arhivistika, 2022)
We often encounter the need to improve properties of museum and archival digitized image material, e.g., resolution, sharpness, contrast, noise level, etc. or eliminate other shortcomings. In the last ten years, artificial intelligence (AI) has been added to editing tools that greatly increase their perceived effectiveness. The paper focuses mainly on the use of algorithms to increase the resolution. The results of a practical test show a noticeable advantage of AI enhanced algorithms. Due to the internal working mechanisms of neural networks, artifacts also occur when AI does not understand the content of the material, when the algorithms are pushed to their limits of capability, when the material under consideration is incompatible with the learning samples or when learning samples contain errors or bias. Archivists will need to pay special attention to providing clarifications on what learning samples and methods have been used and how their quality is controlled, and to draw attention to the possible presence of unwanted artifacts.
Keywords: artificial intelligence; image enhancement and scaling; izboljševanje in skaliranje slikovnega gradiva; machine learing; museum and archival material; muzejsko in arhivsko gradivo; strojno učenje; umetna inteligenca