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pro vyhledávání: '"Wolf, Dominik Werner"'
'A trustworthy representation of uncertainty is desirable and should be considered as a key feature of any machine learning method' (Huellermeier and Waegeman, 2021). This conclusion of Huellermeier et al. underpins the importance of calibrated uncer
Externí odkaz:
http://arxiv.org/abs/2412.13695
A lot of effort is currently invested in safeguarding autonomous driving systems, which heavily rely on deep neural networks for computer vision. We investigate the coupling of different neural network calibration measures with a special focus on the
Externí odkaz:
http://arxiv.org/abs/2406.02411
Autonomous driving perception techniques are typically based on supervised machine learning models that are trained on real-world street data. A typical training process involves capturing images with a single car model and windshield configuration.
Externí odkaz:
http://arxiv.org/abs/2308.11711
Windscreen optical quality is an important aspect of any advanced driver assistance system, and also for future autonomous driving, as today at least some cameras of the sensor suite are situated behind the windscreen. Automotive mass production proc
Externí odkaz:
http://arxiv.org/abs/2305.14513
Publikováno v:
Metrologia; Dec2023, Vol. 60 Issue 6, p1-14, 14p
Autor:
Wolf, Dominik Werner
The purpose of this Master thesis is to explore further possibilities to increase the Luminosity of the Large Hadron Collider (LHC) by improving the optics correction. As a basic principle, turn-by-turn data is measured with BPMs (beam position monit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________65::d88516b38296b15d6a97101e6fad530d
http://cds.cern.ch/record/2759179
http://cds.cern.ch/record/2759179
Publikováno v:
Measurement: Sensors; 20240101, Issue: Preprints