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Document type:
Konferenzbeitrag
Author(s):
Eder, T.; Hachicha, R.; Sellami, H.; van Driesten, C.; Biebl, E.
Title:
Data Driven Radar Detection Models: A Comparison of Artificial Neural Networks and Non Parametric Density Estimators on Synthetically Generated Radar Data
Keywords:
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; Computational modeling; Kernel; Training; Data models
«
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...
»
Book / Congress title:
2019 Kleinheubach Conference
Year:
2019
Month:
Sep.
Pages:
1-4
BibTeX
Occurrences:
mediaTUM Gesamtbestand
Hochschulbibliographie
2019
Fakultäten
Elektrotechnik und Informationstechnik
Höchstfrequenztechnik (Prof. Biebl)
mediaTUM Gesamtbestand
Einrichtungen
Schools
TUM School of Computation, Information and Technology
Departments
Electrical Engineering
Höchstfrequenztechnik (Prof. Biebl)
2019