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Titel:

Data Driven Radar Detection Models: A Comparison of Artificial Neural Networks and Non Parametric Density Estimators on Synthetically Generated Radar Data

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Eder, T.; Hachicha, R.; Sellami, H.; van Driesten, C.; Biebl, E.
Stichworte:
driver information systems; learning (artificial intelligence); mobile robots; neural nets; radar detection; sensors; target tracking; data driven radar detection models; artificial neural networks; nonparametric density estimators; synthetically generated radar data; rapid development; agile development; autonomous driving; functional safety; sensory defects; measurement deviations; incorrect environment model; sensor models; deep generative networks; Radar detection; Mathematical model; Comput...     »
Kongress- / Buchtitel:
2019 Kleinheubach Conference
Jahr:
2019
Monat:
Sep.
Seiten:
1-4
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