Zobrazeno 1 - 7
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pro vyhledávání: '"Vierling, Axel"'
This study investigates the vulnerability of semantic segmentation models to adversarial input perturbations, in the domain of off-road autonomous driving. Despite good performance in generic conditions, the state-of-the-art classifiers are often sus
Externí odkaz:
http://arxiv.org/abs/2402.02154
In recent years, convolutional neural networks (CNNs) are used in a large number of tasks in computer vision. One of them is object detection for autonomous driving. Although CNNs are used widely in many areas, what happens inside the network is stil
Externí odkaz:
http://arxiv.org/abs/2210.07049
This paper addresses the problem of dense depth predictions from sparse distance sensor data and a single camera image on challenging weather conditions. This work explores the significance of different sensor modalities such as camera, Radar, and Li
Externí odkaz:
http://arxiv.org/abs/2012.09667
This paper presents two variations of architecture referred to as RANet and BIRANet. The proposed architecture aims to use radar signal data along with RGB camera images to form a robust detection network that works efficiently, even in variable ligh
Externí odkaz:
http://arxiv.org/abs/2008.13642
We suggest and compare different methods for the numerical solution of Lyapunov like equations with application to control of Markovian jump linear systems. First, we consider fixed point iterations and associated Krylov subspace formulations. Second
Externí odkaz:
http://arxiv.org/abs/1703.04459
Autor:
Vierling, Axel, Groll, Tobias, Meckel, Dennis, Heim, Kristina, Walter, Daniel, Körkemeyer, Dr. Karsten, Berns, Dr. Karsten
Publikováno v:
Construction Robotics; Mar2023, Vol. 7 Issue 1, p53-63, 11p
Akademický článek
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