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Improved and Optimal DBSCAN for Embedded Applications Using High-Resolution Automotive Radar

Santhana Raj, Dipanjan Ghosh

202019 citationsDOI

Abstract

Density Based Spatial Clustering of Applications with Noise (DBSCAN) is the widely used clustering algorithm for automotive radar applications. Many modifications have been proposed across literature. This paper discusses the most effective method of DBSCAN implementation for High-resolution radar applications. Modification of the DBSCAN algorithm for computation and memory optimization especially for an embedded application is discussed in detail in this paper.

Topics & Concepts

DBSCANComputer scienceCluster analysisNoise (video)ComputationRadarAutomotive industryArtificial intelligenceData miningAlgorithmImage (mathematics)EngineeringTelecommunicationsFuzzy clusteringAerospace engineeringCanopy clustering algorithmRadar Systems and Signal ProcessingAdvanced SAR Imaging TechniquesMicrowave Imaging and Scattering Analysis
Improved and Optimal DBSCAN for Embedded Applications Using High-Resolution Automotive Radar | Litcius