Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253794" target="_blank" >RIV/61989100:27240/23:10253794 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10138172" target="_blank" >https://ieeexplore.ieee.org/document/10138172</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2023.3280639" target="_blank" >10.1109/ACCESS.2023.3280639</a>
Alternative languages
Result language
angličtina
Original language name
Digital Restoration of Cultural Heritage With Data-Driven Computing: A Survey
Original language description
Digitized methodologies in the recent era contribute to various fields of automation that used to hold different interests and meanings of human life. Buildings with historical significance, cultural values, and beliefs are becoming an interdisciplinary field of interest, engaging more computer scientists nowadays. Such structures need more attention towards reconstructing their values using a flavor of computerized tools instead of brickwork directly. Due to the wear of time, the tiles and engravings of most of the historical monuments are on the verge of ruin, endangering significant historical values. In this survey, we rebuild the values by delving deep into the device and methodologies by providing a comprehensive understanding of emerging fields and some experimental decisions. We discuss heritage restoration from some essential papers on 3D reconstruction, image inpainting, IoT-based methods, genetic algorithms, and image processing. The survey explains Machine Learning, Deep Learning, and Computer Vision-based methods for various restoration tasks in the related field. We divide this into certain parts contributing to different fields that restore cultural heritage. Moreover, we infer that the techniques will be faster, cheaper, and more beneficial to the context of image reconstruction in the near future.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Access
ISSN
2169-3536
e-ISSN
2169-3536
Volume of the periodical
11
Issue of the periodical within the volume
květen 2023
Country of publishing house
US - UNITED STATES
Number of pages
39
Pages from-to
53939-53977
UT code for WoS article
001005659000001
EID of the result in the Scopus database
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