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Classification of types of road damage using machine learning and a smartwatch
Renssen, Martijn (2019) Classification of types of road damage using machine learning and a smartwatch.
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| Abstract: | The goal of this research is to investigate how accurately machine learning algorithms can classify different types of road damage using accelerometer data from a smartwatch. The accelerometer data is not collected with a real smartwatch, but with a wearable sensor made for motion capture. The types of road damage that were tested with are potholes, cracks and crocodile cracks in asphalt roads only. |
| Item Type: | Essay (Bachelor) |
| Clients: | Unknown organization, Warnsveld |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science, 55 traffic technology, transport technology |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/77794 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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