Description: Electronic Corpus of Karamanlidika Texts: The dataset aims at the electronical publication Karamanlidika texts in both the original Greek writing and Latin transcription and to provide the users with a database which allows the searching and identifiying of phonetic varieties of the indexed lexemes, as well as the finding of grammatical and formational suffixes. Thanks to the indexation of lexemes and morphemes, lexical compatibility can be as easily researched as morphological combinations.

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Description: The Banatica database already contains 1000 bibliographic descriptions and 200 fulltext scanned books. The existing database aim is to facilitate the development and establishment of a virtual database of patrimonial books, accessible on both sides of the border for enabling more efficient cross-border cooperation in educational and research sector. The partners will develop together a common virtual database of rare patrimonial books which can be extended to other type of documents (postal cards, coins, maps) having Banat as a topic, focusing on promotion of common cultural heritage of cross border area, which aim to consolidate the scientific dimension of the intellectuals’ offspring of Banat Region

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Description: Three-dimensional (3-D) inversion of surface Electrical Resistivity Tomography (ERT) data in order to automatically determine a 3-D resistivity subsurface model. The collection contains five datasets.

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Description: AutoGR application is suited for large image datasets, such as the aerial photographs collected with UAVs or during systematic aerial surveys. The GRID system is going to speed up the georeferencing process. AutoGR can be used as online service for image georeferencing.

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Description: The Historical Arabic Documents Dataset for Recognition Systems
Annotation on sub-word level of five books written by different writers from the years 1088-1451.

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Description: CNN Features for Remote Sensing Image Classification
Tools and resources for remote sensing image classification using convolutional neural networks (convnets).
Collection SAT CNN Models contains code and pretrained convnet models for classification of satellite images. The convnets are trained on publicly available SAT-4 and SAT-6 datasets of satellite images (http://csc.lsu.edu/~saikat/deepsat/). Collection contains the following datasets:
- SAT-4 Models - CNN models trained on SAT-4 dataset
- SAT-6 Models - CNN models trained on SAT-6 dataset
- Tools & Results - code for convnet training and image classification, conference paper and presentation

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Description: The Centre for the Study of Ancient Documents was established in 1995 under the auspices of Oxford University's Faculty of Literae Humaniores to provide a focus for the study of ancient documents within Oxford. The Centre provides a home for Oxford University's epigraphical archive, which includes one of the largest collections of squeezes (paper impressions) of Greek inscriptions in the world, together with the Haverfield archive of Roman inscriptions from Britain, and a substantial photographic collection. The strengths of the epigraphical archive lie in its broad coverage of early Greek inscriptions, Attic epigraphy and the Hellenistic world. Individual sites well represented in the archive include Chios, Samos, Priene, Rhodes, and Samothrace. The material in the archive is currently being reorganised and catalogued.

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Description: VISTA - Bibliotheca Alexandrina: Popularize the museum experience by adding many ways to simplify and present archaeological and historical data. By utilizing advance programming and graphics techniques, we aim to make a tool that complements and enriches the real museum, substitutes for the inability to visit it, adds new layers and means of storytelling, connects multiple museums worldwide, and that can be used remotely by anyone in the world. The datagroup consists of one dataset, two documents and two presentations.

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Description: Fourier Transform Infrared Spectra of two sets of samples: 1. Wall paintings 2. Marble Sculpture Scientific Contact: Maram Na'es, Technical University Berlin, Department of Optics and Atomic Physics/ and Synchrotron-light for Experimental Science and Applications in the Middle East (SESAME).

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Description: The metadata schema developed by the Science and Technology for Archaeology Research Center (STARC) has the goal to enable data interoperability and access to the digital resources stored in the local repository. Its structure allows retrieving models, activities, decision and answers the research question on how data can be used for data interpretation and re-used to perform further analysis and post-processing of raw data. The datasets stored in STARC repository refer to 2D and 3D cultural heritage data including archaeological sites, museum objects and architectonic elements. The schema is mostly based on LIDO and CARARE ones and is CIDOC-CRM compliant. The novelty of this metadata schema is the subset of metadata that has been designed to allow recording the information about the provenance of the digital objects, a particularly important aspect when the objects are 3D digital replicas of cultural objects.

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