bibliotek.hv.se
EnglishSvenskaNorsk
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Two-Stage Deep Learning Framework for Road Anomaly Detection and Severity Estimation
University West, Department of Engineering Science.
2025 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2025. , p. 48
Keywords [en]
Road Anomaly Detection, Deep Learning, Computer Vision, Object Detection, Severity Estimation, RF-DETR, U-Net Segmentation, 2D Camera Analysis, Suspension Sensor Data, Autonomous Vehicles
National Category
Robotics and automation
Identifiers
URN: urn:nbn:se:hv:diva-23626Local ID: EXA600OAI: oai:DiVA.org:hv-23626DiVA, id: diva2:1977070
Subject / course
Robotics
Educational program
Master in AI and automation
Supervisors
Examiners
Available from: 2025-06-26 Created: 2025-06-25 Last updated: 2025-09-30Bibliographically approved

Open Access in DiVA

No full text in DiVA

By organisation
Department of Engineering Science
Robotics and automation

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 82 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.47.0
|
WCAG
|
University West Library
|
DiVA portal