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The study introduces the Cloud Computing-based Cultural Heritage Digitization (CCBCHD) framework, a groundbreaking approach that utilizes advanced convolutional neural networks (CNNs) and transfer learning techniques for digitizing and analyzing Han Dynasty portraits. This innovative method addresses the challenges associated with extracting features and symbolically interpreting these culturally significant artworks. CNNs play a crucial role in the CCBCHD system, enabling the efficient extraction of complex features and patterns inherent in the Han Dynasty portraits. These features are essential for understanding the historical and cultural context of the artworks. The integration of transfer learning is another pivotal aspect of this framework. It allows the model to leverage pre-existing knowledge from extensive image datasets, thereby enhancing the accuracy and efficiency of the system in recognizing and interpreting the unique characteristics of these portraits. Moreover, the incorporation of cloud computing within the CCBCHD framework provides scalable computational resources. This scalability is vital for handling extensive data processing and enables real-time analysis, a critical factor in the digitization process. The synergy of deep learning with cloud computing not only ensures precise feature extraction and interpretation but also plays a significant role in preserving and making cultural heritage accessible in the digital domain. This accessibility is particularly important for artworks like the Han Dynasty portraits, which hold immense historical and cultural value. In essence, the CCBCHD framework represents a significant advancement in the field of digital preservation of cultural artifacts. It offers a solution that is not only scalable and efficient but also intelligent, ensuring that the rich legacy of cultural heritage can be preserved and appreciated in the digital era. By adopting such technologies, the study underscores the potential of AI and cloud computing in transforming the ways we preserve, study, and interact with cultural heritage, opening new avenues for exploration and understanding in the realm of art history and conservation. [ABSTRACT FROM AUTHOR]

A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores the potential of web and immersive technologies, specifically the Virtual Romania (VRRO) platform, in enhancing sustainable tourism by redirecting tourist traffic to lesser-known destinations and boosting user engagement through interactive experiences. Our research examines how virtual tourism platforms (VTPs), which include web-based and immersive technologies, support sustainable tourism, complement physical visits, influence user engagement, and foster community building through social features and user-generated content (UGC). An empirical analysis of the VRRO platform reveals high user engagement levels, attributed to its intuitive design and interactive features, regardless of the users' technological familiarity. Our findings also highlight the necessity for ongoing enhancements to maintain user satisfaction. In conclusion, VRRO demonstrates how accessible and innovative technologies in tourism can modernize travel experiences and contribute to the evolution of the broader tourism ecosystem by supporting sustainable practices and fostering community engagement. [ABSTRACT FROM AUTHOR]

Abstract The image classification task of porcelain fragments is of great significance for the digital preservation of cultural heritage. However, common issues are encountered in the image processing of porcelain fragments, including the low computation speed, decreased accuracy due to the uneven distribution of sample categories, and model instability. This study proposes a novel Capsule Network model, referred to as LBCapsNet, which is suitable for the extraction of features from images of porcelain artifacts fragments. A bottleneck-like channel transformation module denoted by ChannelTrans, which resides between the convolutional layer and the PrimaryCaps layer, was first designed. This module is used to reduce the computational complexity and enhance the processing speed when dealing with intricate porcelain images. The MF-R loss function was then proposed by incorporating focal loss into the original loss function. This allows to address the issue of imbalanced distribution of ceramic shard samples and reduce the classification errors, which leads to faster convergence with smoother trend. Finally, an adaptive dynamic routing mechanism is designed with a dynamic learning rate to enhance the overall stability of the classification process. The experimental results obtained on public datasets, such as MNIST, Fashion- MNIST, CIFAR10, FMD and DTD as well as porcelain fragments dataset, demonstrate that LBCapsNet achieves high classification accuracy with faster and more stable computation compared with existing methods. Furthermore, the ability of LBCapsNet to process special textures can provide technical support for the digital preservation and restoration of cultural heritage.

The image classification task of porcelain fragments is of great significance for the digital preservation of cultural heritage. However, common issues are encountered in the image processing of porcelain fragments, including the low computation speed, decreased accuracy due to the uneven distribution of sample categories, and model instability. This study proposes a novel Capsule Network model, referred to as LBCapsNet, which is suitable for the extraction of features from images of porcelain artifacts fragments. A bottleneck-like channel transformation module denoted by ChannelTrans, which resides between the convolutional layer and the PrimaryCaps layer, was first designed. This module is used to reduce the computational complexity and enhance the processing speed when dealing with intricate porcelain images. The MF-R loss function was then proposed by incorporating focal loss into the original loss function. This allows to address the issue of imbalanced distribution of ceramic shard samples and reduce the classification errors, which leads to faster convergence with smoother trend. Finally, an adaptive dynamic routing mechanism is designed with a dynamic learning rate to enhance the overall stability of the classification process. The experimental results obtained on public datasets, such as MNIST, Fashion- MNIST, CIFAR10, FMD and DTD as well as porcelain fragments dataset, demonstrate that LBCapsNet achieves high classification accuracy with faster and more stable computation compared with existing methods. Furthermore, the ability of LBCapsNet to process special textures can provide technical support for the digital preservation and restoration of cultural heritage. [ABSTRACT FROM AUTHOR]

A sustainable smart tourism ecosystem relies on building digital networks that link tourists to destinations. This study explores the potential of web and immersive technologies, specifically the Virtual Romania (VRRO) platform, in enhancing sustainable tourism by redirecting tourist traffic to lesser-known destinations and boosting user engagement through interactive experiences. Our research examines how virtual tourism platforms (VTPs), which include web-based and immersive technologies, support sustainable tourism, complement physical visits, influence user engagement, and foster community building through social features and user-generated content (UGC). An empirical analysis of the VRRO platform reveals high user engagement levels, attributed to its intuitive design and interactive features, regardless of the users’ technological familiarity. Our findings also highlight the necessity for ongoing enhancements to maintain user satisfaction. In conclusion, VRRO demonstrates how accessible and innovative technologies in tourism can modernize travel experiences and contribute to the evolution of the broader tourism ecosystem by supporting sustainable practices and fostering community engagement.

The demand for digitized cultural heritage has increased over the last few decades; digitization is indeed considered a powerful means to preserve and enhance cultural heritage and make it accessible to the wider public for education and research purposes. However, digitizing cultural heritage is a complex process, requiring specific competencies, skills, software, technologies, and, therefore, human and financial resources. Cultural organizations are therefore rethinking their traditional business models, often deciding to outsource their digitization projects or implementing PPPs—public–private partnerships. This is particularly evident in developing countries, where it is also challenging to find the required resources locally and international cooperation is sometimes necessary. However, international PPPs for the digitization of cultural heritage present several unsustainable aspects. There is therefore a need for a deeper understanding of which practices should be implemented to sustainably manage these collaborations. This paper aims to investigate this topic using a case study analysis of two international PPPs for the digitization of cultural heritage in Brazil. The analysis highlights relevant managerial choices that led these projects to positively impact local social, economic, and environmental development, thus bringing early insights to advance the academic and practice discussions on the above-mentioned topic. [ABSTRACT FROM AUTHOR]

A portable, user-friendly multispectral imaging system assembled almost entirely of common photography equipment and open-source software has been developed. The system serves as an outreach and educational tool for demonstrating and promoting scientific imaging as a more routine practice in the contexts of cultural heritage digitization and photography. These efforts are aimed primarily at institutions where advanced imaging technologies are not already found, and where funding and expertise may limit access to commercial, bespoke multispectral imaging solutions that are currently available. The background and theory that were shared in tutorials given during the system’s initial testing campaign are detailed here. Testing was carried out in one-day on-site visits to six cooperating institutions of different sizes and collection types in the northeast USA. During these visits, the imaging system was presented, and the benefit of collecting spectral data using low barrier-to-entry capture and processing methods relative to conventional imaging methods was discussed. Imaging was conducted on site on selected collections objects to showcase the current capabilities of the system and to inform ongoing improvements to the setup and processing. This paper is a written companion piece to the visits, as a source of further detail and context for the two-light imaging system that was described and demonstrated.

A portable, user-friendly multispectral imaging system assembled almost entirely of common photography equipment and open-source software has been developed. The system serves as an outreach and educational tool for demonstrating and promoting scientific imaging as a more routine practice in the contexts of cultural heritage digitization and photography. These efforts are aimed primarily at institutions where advanced imaging technologies are not already found, and where funding and expertise may limit access to commercial, bespoke multispectral imaging solutions that are currently available. The background and theory that were shared in tutorials given during the system's initial testing campaign are detailed here. Testing was carried out in one-day on-site visits to six cooperating institutions of different sizes and collection types in the northeast USA. During these visits, the imaging system was presented, and the benefit of collecting spectral data using low barrier-to-entry capture and processing methods relative to conventional imaging methods was discussed. Imaging was conducted on site on selected collections objects to showcase the current capabilities of the system and to inform ongoing improvements to the setup and processing. This paper is a written companion piece to the visits, as a source of further detail and context for the two-light imaging system that was described and demonstrated. [ABSTRACT FROM AUTHOR]

Die Kulturgutdigitalisierung gehört seit Jahren zum Kerngeschäft der Landesbibliotheken wie der BLB. Dabei lag der Fokus lange Zeit auf der Contentdigitalisierung von unikalem Material. Hinzu kamen regional interessante Bestände wie Adressbücher oder Landtagsprotokolle. Allerdings stellt sich zunehmend die Frage, ob die Aufgabe der Bibliotheken mit der reinen Imageproduktion schon erledigt ist. Am Beispiel der BLB sollen Zukunftsperspektiven aufgezeigt werden, die über die Contentproduktion hinausgehen. Dazu gehört neben der Anreicherung der Digitalisate durch Normdaten, Volltexte und Editionen die Einbindung in überregionale Portale, die Zusammenarbeit mit der Forschung bei ausgewählten Projekten, die Unterstützung kleinerer Einrichtungen und das Engagement in Citizen-Science-Projekten. Digitizing the cultural heritage has been a central task of state libraries like the BLB for many years. Initially, the focus was on content digitization of unique material. Regionally interesting holdings such as address books or regional parliament protocols were added. The question, however, is whether the task of libraries is fully accomplished by producing digital images. Using the example of the Baden State Library, future perspectives will be illustrated that extend far beyond content production. Alongside enriching the digitized material with standard data, full texts and editions, this also includes integration into national portals, cooperations with scientific research in selected projects, support for small-scale institutions and engaging in citizen-science projects. [ABSTRACT FROM AUTHOR]

We have developed a procedure to achieve a high accuracy of color capture for digital still cameras for cultural heritage digitization. The procedure uses a standard color target and additional spectral measurements directly on the artwork. A set of complementary colors is determined thanks to an initial analysis of the digital image and a comparison with the standard color target. The developed procedure results in a digital copy that better represents the colors of the original than using only standard color targets. [ABSTRACT FROM AUTHOR]

In the context of digitization of photographs and other documents with graphical value, cultural heritage organizations need to give a guarantee that the stored digital image is a faithful representation of the physical image both at the physical level and the perceptual level. On the physical level, image quality can be measured objectively in a simple way by applying certain physical attributes to the image, as well as by measuring how distorting images affects the performance of the attributes. However, on the perceptual level, image quality should correspond to the perception that a human expert would experience when observing the physical image under certain determined and controlled conditions. In this paper we address the problem of image quality assessment (IQA) in the context of cultural heritage digitization by applying machine learning (ML). In particular, we explore the possibility of creating a decision tree that mimics the response of an expert on cultural heritage when observing cultural heritage images. [ABSTRACT FROM AUTHOR]

A workflow for the color reproduction of digital still images for the purpose of cultural heritage digitization is presented. An analysis was performed to determine the effect of RAW to TIFF transformation; RGB to CIE L*a*b* transformation; white balancing; use of standard color spaces: sRGB, AdobeRGB (1998), ProPhoto RGB, eciRGBv2; custom DCP, and ICC profiles assigning. For the analysis, Color Checker Classic and Digital Color Checker SG targets were used. The precision of the color reproduction was checked against FADGI and Metamorfoze standards. We demonstrate that to obtain high color fidelity reproduction, white balancing and a custom ICC profile are necessary, while DCP profiling could be omitted. [ABSTRACT FROM AUTHOR]

The digitization of Cultural Heritage assumes an interdisciplinary approach, collaborative knowledge co-creation, and distant communication. This can only be fulfilled by ICT means requiring in turn alignment between those who deliver the technical (IT) support and those who are in the role users. A Service-Oriented approach is considered adequate in this regard because of users’ composing services at high level (with underlying technical complexity remaining hidden) and developers’ considering the software components whose functionality is delivered through the services. All this requires however complex regulations to conform with. Semiotic norms in combination with workflows are considered in this regard. In this paper, we propose an approach based on Service-Oriented Computing and Organizational Semiotics, directed to Cultural Heritage digitization. The approach is partially illustrated by means of an example.

Abstract: Fully automated three-dimensional (3D) measurement (either with contact or non-contact measurement heads) cannot be easily completed without detailed a priori knowledge of the measured object. This requirement may be easily fulfilled for objects whose CAD models are available (for example, mechanical parts); however, for unique artifacts (such as sculptures), such models are usually unavailable. A description of the object’s shape is required to create a list of positions at which the scanning head should be placed to completely measure the whole object (so-called next best views list). For unique objects, this analysis has to be performed on-line during measurements, using obtained data to update the list. For a fully automated measurement, the scanning system must be positioned mechanically, and the transition between subsequent head positions has to be collision free. This paper presents a novel system for 3D digitization of cultural heritage objects which allows one to perform completely automated shape measurements in a given volume with sampling resolutions up to 10000 points/ mm2. Its main novelties are the next best view module for identifying the best position and orientation of the measurement head in subsequent directional scans (optimized for artifacts of size much bigger than the measurement volume) and flexible software modules for inverse kinematics and collision detection, which allow one to build a positioning system tailored to specific measurement objects. The system is used for digitization of a collection from the Wilanow Palace Museum, Warsaw. [Copyright &y& Elsevier]

The paper identifies necessary steps to create a national information system for management and preservation of cultural heritage documentation. The Republic of Serbia, where the digitization of cultural heritage is recognized as a segment of cultural development and officially accepted as one of the methods for preservation and presentation of heritage documentation, is taken as a case study. The paper describes the evolutionary path of the digitization process in Serbia and analyzes the importance of the adoption of a legal framework and establishment of national standards in the process of achieving the uniqueness in cultural heritage long-term sustainable documentation management and preservation across cultural institutions. [ABSTRACT FROM AUTHOR]