Detection of road surface defects from data acquired by a laser scanner

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU140776" target="_blank" >RIV/00216305:26220/21:PU140776 - isvavai.cz</a>
Result on the web
<a href="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_2.pdf" target="_blank" >https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_2.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Detection of road surface defects from data acquired by a laser scanner
Original language description
Research in the field of automatic detection of road surface defects has been relatively widespread in recent years. Most of the existing works solve this issue by processing the image acquired by camera technology. The contribution of this study is the proposal of the LRS-CNN algorithm for the detection of defects on road surfaces based on their laser scans. The advantage of LRS-CNN is the ability to detect so-called microcracks, which can not be recognized from camera recordings. We have also found that transfer learning methods are not suitable for the use of road defect detection from their laser scans. Our LRS-CNN algorithm has been trained on unique nonpublic data and is able to achieve up to 99.33 % of success depending on the type of task.
Czech name
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Czech description
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Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings II of the 27th Conference STUDENT EEICT 2021
ISBN
978-80-214-5943-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
275-279
Publisher name
Brno Univeristy of Technology, Faculty of Electrical Engineering and Communication
Place of publication
Brno, Czech Republic
Event location
Brno
Event date
Apr 27, 2021
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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