An unique dataset for Christian sacral objects identification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12210%2F23%3A43906426" target="_blank" >RIV/60076658:12210/23:43906426 - isvavai.cz</a>
Alternative codes found
RIV/60076658:12310/23:43906426
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2352340923002561?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352340923002561?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.dib.2023.109137" target="_blank" >10.1016/j.dib.2023.109137</a>

Result language
angličtina
Original language name
An unique dataset for Christian sacral objects identification
Original language description
Christian religious monuments as cathedrals, chapels, and temples, are found in many places on our planet. Worldfamous buildings such as the Notre Dame Cathedral in Paris, Gaudi's Cathedral in Barcelona, and St. Vitus Cathedral in Prague are commonly known. Many online photographs can be used to build machine-learning models to identify them. The number of photographs is already significantly lower for little-known buildings, such as small churches in the Czech-German border region, and similar approaches cannot be used for identification. Based on these facts, our team has compiled a unique dataset for identifying the most important elements of Christian sacral buildings as altars, frescoes, pulpits, etc., which are almost always found in them. Our data set was manually created from several thousand real photographs. This dataset seems to be very usable, e.g., for creating new machine learning models and identifying objects in sacred objects or the objects themselves. (c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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