In this article we shed light on the position of Finland in conversations on the movement of unprovenanced cultural objects, within the national, the Nordic and the global contexts. Finland’s geopolitical position, as a ‘hard border’ of the European Union neighbouring the Russian Federation, and its current legislative provisions which do not include import regulation, mean that nonetheless has the potential to be significant in understanding the movement of cultural property at transnational levels. In particular, we outline a recent initiative started at the University of Helsinki to kick-start a national debate on ethical working with cultural object and manuscripts. We analyse exploratory research on current awareness and opinion within Finland, and summarize our current work to produce robust research ethics to guide scholars working in Finland. Although Finland has a small population and is usually absent from international discussions on the illicit movement of cultural property (save a few exceptions), we argue that it is still possible — and important — to affect policy and attitudes concerning art crime, provenance, and the role of stakeholders such as decision-makers, traders and the academy.

The automatic recognition of scanned Medieval manuscripts still represents a challenge due to degradation, non standard layouts, or notations. This paper focuses on the Medieval square notation developed around the 11th century which is composed of staff lines, clefs, accidentals, and neumes which are basically connected single notes. We present a novel approach to tackle the automatic transcription by applying CNN/LSTM networks that are trained using the segmentation-free CTC-loss-function which considerably facilitates the GT-production. For evaluation, we use three different manuscripts and achieve a dSAR of 86.0% on the most difficult book and 92.2% on the cleanest one. To further improve the results, we apply a neume dictionary during decoding which yields a relative improvement of about 5%.

Even today, the automatic digitisation of scanned documents in general but especially the automatic optical music recognition (OMR) of historical manuscripts still remain an enormous challenge, since both handwritten musical symbols and text have to be identified. This paper focuses on the Medieval so-called square notation developed in the 11th-12th century, which is already composed of staff lines, staves, clefs, accidentals, and neumes, that are roughly spoken connected single notes. The aim is to develop an algorithm that captures both the neume and pitch, that is melody information that can be used to reconstruct the original writing. Our pipeline is similar to the standard OMR approach and comprises a novel staff line and symbol detection algorithm, based on deep Fully Convolutional Networks (FCN), which perform pixel-based predictions for either staff lines or symbols and their respective types. Then, the staff line detection combines the extracted lines to staves and yields an F1-score of over 99% for both detecting lines and complete staves. For the music symbol detection we choose a novel approach that skips the step to identify neumes and instead directly predicts note components (NCs) and their respective affiliation to a neume. Furthermore, the algorithm detects clefs and accidentals. Our algorithm recognises these symbols with an F1-score of over 96% if the type is ignored and predicts the true symbol sequence of a staff with a diplomatic symbol accuracy rate (dSAR) of about 87%. If only the NCs without their respective connection to a neume, all clefs, and accidentals are of interest the algorithm reaches an harmonic symbol accuracy rate (hSAR) of approximately 90%.

This paper discusses a cross-disciplinary, international collaboration aimed at researching a series of 15th century choir books at the abbey of San Giorgio Maggiore on the homonymous island in Venice. Produced for the abbey itself, the books have never left the island during their 500-years history, thereby allowing a unique opportunity to analyse historic artefacts, which have undergone little modification over time. Prompted by ongoing cataloguing work on the manuscripts, a week-long analytical campaign using a combination of non-invasive analytical methods used in portable configuration allowed the comprehensive characterisation of ten volumes. The manuscripts’ palette and painting techniques were analysed using near-infrared imaging, reflectance spectroscopy in the UV-vis-NIR range, Raman spectroscopy, X-ray fluorescence mapping and digital microscopy. The paper will discuss the challenges linked to the fragility and the large dimensions of the volumes as well as the most interesting results of the investigation. These include the detection of unusual painting materials such as bismuth ink, as well as the discovery of a less homogeneous palette than originally expected, which prompted a partial revision of the attribution of the decoration in one of the volumes to a single artist.

Transformers are increasing replacing older generation of deep neural networks due to their success in a wide range of application. The dominant approach of using transformers is to pre-train them on a large training dataset and then fine-tune them on a downstream task. However, as transformers becoming larger, the fine-tuning approach is become an infeasible approach for transfer learning. In this short survey, we list a few recent methods that makes using transformers based on transfer learning more efficient.

The Privilegium maius is one of the most famous and spectacular forgeries in medieval Europe. It is a set of charters made in 14th century upon commitment by duke Rudolf IV, a member of the Habsburg family, to elevate the rank and the prestige of his family. These five charters, now kept at the Österreichisches Staatsarchiv in Vienna, have been subjected to a thorough interdisciplinary study in order to shed light on its controversial story. The charters are composed by pergamenaceous documents bound to wax seals with coloured textile threads. The present contribution concerns the characterisation of the inks used for writing and of the dyes used to colour to the threads: are they compatible with the presumed age of the charters? Though showing only a part of the whole story of the charters, dyes analysis could contribute in assessing their complex history from manufacturing to nowadays. The dyes were characterised with non-invasive in situ measurements by means of FORS and with micro-invasive measurements by means of SERS and HPLC-MS analysis. The results showed that the threads of four of the charters (three dyed with madder, one with orchil) were apparently coloured at different dyeing stages, then re-dyed in the 19th-20th century.