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Leveraging Supervised Learning for Effective Road Anomaly Detection and Severity Estimation
Al-Eryani, Aws
University West, Department of Engineering Science.
2025 (English)
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Abstract [en]
See separate file
Place, publisher, year, edition, pages
2025. , p. 48
Keywords [en]
Road Anomaly Detection, Anomaly Severity Estimation, Deep Learning, Segmentation, Object Detection, Regression, Machine Learning
National Category
Robotics and automation
Identifiers
URN:
urn:nbn:se:hv:diva-23623
Local ID: EXA600
OAI: oai:DiVA.org:hv-23623
DiVA, id:
diva2:1977054
Subject / course
Robotics
Educational program
Master in AI and automation
Supervisors
Ali, Rashid
University West, Department of Engineering Science, Division of computer engineering and computer science.
Examiners
Nilsen, Morgan
University West, Department of Engineering Science, Division of industrial automation.
Available from:
2025-06-26
Created:
2025-06-25
Last updated:
2025-06-26
Bibliographically approved
Open Access in DiVA
Abstract
(27 kB)
11 downloads
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FULLTEXT02.pdf
File size
27 kB
Checksum
SHA-512
3c4333599bfad6bc7ced040e71af26ab1b04cc2dc0929e685e1491568435e30b6e933a2a36272607efe887be97dce84c1108fd8df962ed0485fa6200ed58c76d
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fulltext
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application/pdf
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Department of Engineering Science
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Robotics and automation
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Total: 11 downloads
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apa
ieee
modern-language-association-8th-edition
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de-DE
en-GB
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