Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Oliver Wasenmuller"'
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2781 (2024)
Detecting vulnerable road users is a major challenge for autonomous vehicles due to their small size. Various sensor modalities have been investigated, including mono or stereo cameras and 3D LiDAR sensors, which are limited by environmental conditio
Externí odkaz:
https://doaj.org/article/4614b3a38d4c4645ab633c94b0cf5b6a
Publikováno v:
Sensors, Vol 23, Iss 7, p 3447 (2023)
Recently, transformer architectures have shown superior performance compared to their CNN counterparts in many computer vision tasks. The self-attention mechanism enables transformer networks to connect visual dependencies over short as well as long
Externí odkaz:
https://doaj.org/article/080a64f825074ea089f9ad7f8687996c
Publikováno v:
2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f08ee3f40f574eedbcab2181b82e1be5
https://doi.org/10.1109/ismar-adjunct57072.2022.00180
https://doi.org/10.1109/ismar-adjunct57072.2022.00180
In order to ensure safe autonomous driving, precise information about the conditions in and around the vehicle must be available. Accordingly, the monitoring of occupants and objects inside the vehicle is crucial. In the state-of-the-art, single or m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::197476f0f589a5d23d5fd027ce8af258
http://arxiv.org/abs/2205.01515
http://arxiv.org/abs/2205.01515
Publikováno v:
ITSC
Depth completion from sparse LiDAR and high-resolution RGB data is one of the foundations for autonomous driving techniques. Current approaches often rely on CNN-based methods with several known drawbacks: flying pixel at depth discontinuities, overf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85249280daa40e5865971b3e54f827fb
http://arxiv.org/abs/2107.06711
http://arxiv.org/abs/2107.06711
Publikováno v:
ICPR
Ghost targets are targets that appear at wrong locations in radar data and are caused by the presence of multiple indirect reflections between the target and the sensor. In this work, we introduce the first point based deep learning approach for ghos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf74ab36a7c88b738bc36d91987c1545
https://doi.org/10.1109/icpr48806.2021.9413247
https://doi.org/10.1109/icpr48806.2021.9413247