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Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework

Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework

Daniel Bauer
L. Kuhnert
L. Eckstein
    EDL
ArXiv (abs)PDFHTML

Papers citing "Deep, spatially coherent Inverse Sensor Models with Uncertainty Incorporation using the evidential Framework"

6 / 6 papers shown
Title
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction
Masha Itkina
Mykel J. Kochenderfer
EDLUQCV
107
26
0
16 Nov 2022
Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data
Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data
Raphael van Kempen
Bastian Lampe
Lennart Reiher
Timo Woopen
Till Beemelmanns
L. Eckstein
44
1
0
15 Nov 2022
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping
Raphael van Kempen
Bastian Lampe
Timo Woopen
L. Eckstein
33
10
0
25 Feb 2021
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping
Deep Inverse Sensor Models as Priors for evidential Occupancy Mapping
Daniel Bauer
L. Kuhnert
L. Eckstein
15
5
0
02 Dec 2020
Deep Open Space Segmentation using Automotive Radar
Deep Open Space Segmentation using Automotive Radar
F. Nowruzi
Dhanvin Kolhatkar
Prince Kapoor
Fahed Al Hassanat
E. J. Heravi
R. Laganière
Julien Rebut
Waqas Malik
46
26
0
18 Mar 2020
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
Zepeng Huo
Arash Pakbin
Xiaohan Chen
N. Hurley
Ye Yuan
Xiaoning Qian
Zhangyang Wang
Shuai Huang
B. Mortazavi
HAI
46
11
0
03 Mar 2020