Shan et al., 2024 - Google Patents
Unmanned aerial vehicle (UAV)-Based pavement image stitching without occlusion, crack semantic segmentation, and quantificationShan et al., 2024
View PDF- Document ID
- 8324643226960999683
- Author
- Shan J
- Jiang W
- Huang Y
- Yuan D
- Liu Y
- Publication year
- Publication venue
- IEEE Transactions on Intelligent Transportation Systems
External Links
Snippet
Unmanned Aerial Vehicle (UAV)-based pavement distress detection offers efficient and safe advantages. However, obstructions from road vehicles and the slender shape of cracks in UAV images challenge accuracy. To address this, this study established specific flight …
- 230000011218 segmentation 0 title description 63
Classifications
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- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
- G06K9/00818—Recognising traffic signs
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
- G06K9/00798—Recognition of lanes or road borders, e.g. of lane markings, or recognition of driver's driving pattern in relation to lanes perceived from the vehicle; Analysis of car trajectory relative to detected road
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06T2207/30108—Industrial image inspection
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