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Lidar–camera semi-s...
Lidar–camera semi-supervised learning for semantic segmentation
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- Caltagirone, Luca, 1983 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Bellone, Mauro, 1982 (författare)
- Tallinna Tehnikaülikool (TalTech),Tallinn University of Technology (TalTech)
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- Svensson, Lennart, 1976 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wahde, Mattias, 1969 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Sell, Raivo (författare)
- Tallinna Tehnikaülikool (TalTech),Tallinn University of Technology (TalTech)
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(creator_code:org_t)
- 2021-07-14
- 2021
- Engelska.
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Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:14
- Relaterad länk:
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https://research.cha... (primary) (free)
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https://www.mdpi.com...
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https://research.cha...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- In this work, we investigated two issues: (1) How the fusion of lidar and camera data can improve semantic segmentation performance compared with the individual sensor modalities in a supervised learning context; and (2) How fusion can also be leveraged for semi-supervised learning in order to further improve performance and to adapt to new domains without requiring any additional labelled data. A comparative study was carried out by providing an experimental evaluation on networks trained in different setups using various scenarios from sunny days to rainy night scenes. The networks were tested for challenging, and less common, scenarios where cameras or lidars individually would not provide a reliable prediction. Our results suggest that semi-supervised learning and fusion techniques increase the overall performance of the network in challenging scenarios using less data annotations.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Sensor fusion
- Semantic segmentation
- Deep learning
- Semi-supervised learning
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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