Road Quality Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F22%3A00358063" target="_blank" >RIV/68407700:21240/22:00358063 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-06430-2_46" target="_blank" >https://doi.org/10.1007/978-3-031-06430-2_46</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-06430-2_46" target="_blank" >10.1007/978-3-031-06430-2_46</a>
Alternative languages
Result language
angličtina
Original language name
Road Quality Classification
Original language description
Road quality significantly influences safety and comfort while driving. Especially for most kinds of two-wheelers, road damage is a real threat, where vehicle components and enjoyment are heavily impacted by road quality. This can be avoided by planning a route considering the surface quality. We propose a new publicly available and manually annotated dataset collected from Google Street View photos. This dataset is devoted to a road quality classification task considering six levels of damage. We evaluated some preprocessing methods such as shadow removal, CLAHE, and data augmentation. We adapted several pre-trained networks to classify road quality. The best performance was reached by MobileNet using augmented dataset (75.55%).
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA18-18080S" target="_blank" >GA18-18080S: Fusion-Based Knowledge Discovery in Human Activity Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis and Processing – ICIAP 2022
ISBN
978-3-031-06430-2
ISSN
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e-ISSN
1611-3349
Number of pages
11
Pages from-to
553-563
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Lecce
Event date
May 23, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000870296100046