Machine learning to boost the next generation of visualization technology

Research output: Contribution to journalArticle

32 Scopus citations

Abstract

Many visualization systems do not get widespread adoption because they confront the user with sophisticated operations and interfaces. The author suggests augmenting visualization systems with learning capability to improve both the performance and usability of visualization systems. Several examples including volume segmentation, flow feature extraction, and network security are given illustrating how machine learning can help streamline the process of visualization, simplify the user interface and interaction, and support collaborative work.

Original languageEnglish (US)
Pages (from-to)6-9
Number of pages4
JournalIEEE Computer Graphics and Applications
Volume27
Issue number5
DOIs
StatePublished - Sep 1 2007

Keywords

  • Information visualization
  • Intelligent systems
  • Interface design
  • Machine learning
  • Scientific visualization

ASJC Scopus subject areas

  • Software
  • Medicine(all)
  • Computer Graphics and Computer-Aided Design

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