Constraint-Based Hierarchical Cluster Selection in Automotive Radar Data

Constraint-Based Hierarchical Cluster Selection in Automotive Radar Data

High-resolution automotive radar sensors play an increasing role in detection, classification and tracking of moving objects in traffic scenes. Clustering is frequently used to group detection points in this context. However, this is a particularly challenging task due to variations in number and de...

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Bibliographic Details
Main Authors:	Claudia Malzer, Marcus Baum
Format:	Article
Language:	English
Published:	MDPI AG 2021-05-01
Series:	Sensors
Subjects:	hierarchical clustering HDBSCAN constraint-based clustering semi-supervised clustering automotive radar
Online Access:	https://www.mdpi.com/1424-8220/21/10/3410

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