RECONSTRUCTION OF CONCRETE MORPHOLOGY USING DEEP LEARNING

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F24%3A00382865" target="_blank" >RIV/68407700:21110/24:00382865 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.14311/APP.2024.49.0085" target="_blank" >http://dx.doi.org/10.14311/APP.2024.49.0085</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/APP.2024.49.0085" target="_blank" >10.14311/APP.2024.49.0085</a>

Result language

angličtina

Original language name

RECONSTRUCTION OF CONCRETE MORPHOLOGY USING DEEP LEARNING

Original language description

In this contribution, the concrete morphology is reconstructed with a simple algorithm selecting a pixel value based on the small set of surrounding pixels. A deep neural network (DNN) is used as a classifier, and the authors focus on studying different DNN architectures. The performance of the proposed algorithm is evaluated on several statistical descriptors and the grain size distribution curve.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

20101 - Civil engineering

Project

<a href="/en/project/GF22-35755K" target="_blank" >GF22-35755K: SUMO: Sustainable design empowered by materials modelling, semantic interoperability and multi-criteria optimization</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Acta Polytechnica CTU Proceedings

ISBN

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ISSN

2336-5382

e-ISSN

2336-5382

Number of pages

7

Pages from-to

85-91

Publisher name

CESKE VYSOKE UCENI TECHNICKE V PRAZE

Place of publication

Praha

Event location

Praha

Event date

Sep 14, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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