Computer Vision-Based Algorithms for Recognition of Construction and Demolition Waste Materials
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F23%3A00368862" target="_blank" >RIV/68407700:21110/23:00368862 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.4028/p-mj94xc" target="_blank" >https://doi.org/10.4028/p-mj94xc</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4028/p-mj94xc" target="_blank" >10.4028/p-mj94xc</a>
Alternative languages
Result language
angličtina
Original language name
Computer Vision-Based Algorithms for Recognition of Construction and Demolition Waste Materials
Original language description
The construction industry generates a significant amount of waste, posing challenges for efficient waste management and resource recovery. this paper presents a preliminary study on the use of lightweight computer vision (cv) algorithms for the automatic recognition of construction and demolition waste (cdw) materials. utilizing image datasets acquired by drones, the study aims to develop strategies for distinguishing between individual cdw materials based on the mean intensity gradient, brightness, and relative representation of color channels. results indicate that the proposed method can effectively recognize crucial cdw materials, paving the way for potential applications in industry and geodesy. further research is needed to test additional materials and metrics to refine the method for practical implementation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
21100 - Other engineering and technologies
Result continuities
Project
<a href="/en/project/SS03010302" target="_blank" >SS03010302: Development of efficient tools to minimize production of construction and demolition waste, its monitoring and reuse</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Science and Technology
ISBN
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ISSN
1662-8969
e-ISSN
1662-0356
Number of pages
7
Pages from-to
11-17
Publisher name
Trans Tech Publications Ltd
Place of publication
Durnten-Zurich
Event location
Brunel University London-UK
Event date
Jul 11, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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