Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Stefan Elser"'
Publikováno v:
Journal of Imaging, Vol 10, Iss 10, p 246 (2024)
Time-of-Flight (ToF) cameras are subject to high levels of noise and errors due to Multi-Path-Interference (MPI). To correct these errors, algorithms and neuronal networks require training data. However, the limited availability of real data has led
Externí odkaz:
https://doaj.org/article/cef3664e0c264f5bb9f1f0f83911771f
Publikováno v:
Journal of Imaging, Vol 10, Iss 8, p 198 (2024)
In this paper, we present a multi-task model that predicts disparities and confidence levels in deep stereo matching simultaneously. We do this by combining its successful model for each separate task and obtaining a multi-task model that can be trai
Externí odkaz:
https://doaj.org/article/782eb5addd6c4aee9196587c0b1dd82e
Publikováno v:
IEEE Sensors Journal. 22:2735-2743
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d698bce3d87454de49dc01f269fb234
https://doi.org/10.1109/jsen.2021.3136362
https://doi.org/10.1109/jsen.2021.3136362
Publikováno v:
IEEE Transactions on Biomedical Engineering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20ae628d6bd44d3b2b745fca6e31b4eb
Publikováno v:
at - Automatisierungstechnik. 69:499-510
Measuring the similarity between point clouds is required in many areas. In autonomous driving, point clouds for 3D perception are estimated from camera images but these estimations are error-prone. Furthermore, there is a lack of measures for qualit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14ced780b4711ad34afaf656f800de08
https://doi.org/10.1515/auto-2020-0140
https://doi.org/10.1515/auto-2020-0140
Sensory data is essential for the training of methods in autonomous driving like object detection, odometry, or SLAM. MEMS LiDAR sensors can be very valuable for autonomous vehicles because they are less prone to shock and wear compared to motorized
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b769c01529a4e50d131a3dabd3ead69
https://doi.org/10.36227/techrxiv.19615563.v2
https://doi.org/10.36227/techrxiv.19615563.v2
Publikováno v:
at - Automatisierungstechnik. 67:545-556
In autonomous driving, prediction tasks address complex spatio-temporal data. This article describes the examination of Recurrent Neural Networks (RNNs) for object trajectory prediction in the image space. The proposed methods enhance the performance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1011b7af6c490e246cd496c65c45f21
https://doi.org/10.1515/auto-2018-0124
https://doi.org/10.1515/auto-2018-0124