Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data

Dimensionality Reduction and Subspace Clustering in Mixed Reality for Condition Monitoring of High-Dimensional Production Data

Visual analytics are becoming increasingly important in the light of big data and related scenarios. Along this trend, the field of immersive analytics has been variously furthered as it is able to provide sophisticated visual data analytics on one hand, while preserving user-friendliness on the oth...

Full description

Bibliographic Details
Main Authors: Burkhard Hoppenstedt, Manfred Reichert, Klaus Kammerer, Thomas Probst, Winfried Schlee, Myra Spiliopoulou, Rüdiger Pryss
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Sensors
Subjects:
immersive analytics
dimensionality reduction
mixed reality
covariance graph
subspace clustering
Online Access:https://www.mdpi.com/1424-8220/19/18/3903

Internet

https://www.mdpi.com/1424-8220/19/18/3903

Similar Items