Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Gotzig, Heinrich"'
Autor:
Mohapatra, Sambit, Yogamani, Senthil, Kumar, Varun Ravi, Milz, Stefan, Gotzig, Heinrich, Mäder, Patrick
LiDAR is crucial for robust 3D scene perception in autonomous driving. LiDAR perception has the largest body of literature after camera perception. However, multi-task learning across tasks like detection, segmentation, and motion estimation using Li
Externí odkaz:
http://arxiv.org/abs/2307.08850
Publikováno v:
Proceedings of the 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
Indirect Time of Flight LiDARs can indirectly calculate the scene's depth from the phase shift angle between transmitted and received laser signals with amplitudes modulated at a predefined frequency. Unfortunately, this method generates ambiguity in
Externí odkaz:
http://arxiv.org/abs/2304.07047
Autor:
Mohapatra, Sambit, Mesquida, Thomas, Hodaei, Mona, Yogamani, Senthil, Gotzig, Heinrich, Mader, Patrick
Spiking Neural Networks are a recent and new neural network design approach that promises tremendous improvements in power efficiency, computation efficiency, and processing latency. They do so by using asynchronous spike-based data flow, event-based
Externí odkaz:
http://arxiv.org/abs/2206.02876
In this paper, a deep learning approach is presented for direction of arrival estimation using automotive-grade ultrasonic sensors which are used for driving assistance systems such as automatic parking. A study and implementation of the state of the
Externí odkaz:
http://arxiv.org/abs/2202.12684
Autor:
Mohapatra, Sambit, Hodaei, Mona, Yogamani, Senthil, Milz, Stefan, Gotzig, Heinrich, Simon, Martin, Rashed, Hazem, Maeder, Patrick
Moving object detection and segmentation is an essential task in the Autonomous Driving pipeline. Detecting and isolating static and moving components of a vehicle's surroundings are particularly crucial in path planning and localization tasks. This
Externí odkaz:
http://arxiv.org/abs/2111.04875
3D object detection based on LiDAR point clouds is a crucial module in autonomous driving particularly for long range sensing. Most of the research is focused on achieving higher accuracy and these models are not optimized for deployment on embedded
Externí odkaz:
http://arxiv.org/abs/2104.10780
Neural networks have become the standard model for various computer vision tasks in automated driving including semantic segmentation, moving object detection, depth estimation, visual odometry, etc. The main flavors of neural networks which are used
Externí odkaz:
http://arxiv.org/abs/1903.02080
Publikováno v:
24th International Workshop on Thermal Investigations of ICs and Systems THERMINIC-2018
This paper proposes the replacement of a conventional Insulating-Metal-Substrate (IMS) dielectric layer with an electroconductive adhesive which is applied onto a treated aluminium heat sink. The adhesive based structure results in a lower thermal re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::a989cc92f7613cd8458751af3a1c63a5
Autor:
Gotzig, Heinrich, Geduld, Georg
Publikováno v:
Handbook of Driver Assistance Systems; 2016, p405-430, 26p
