Machine learning to boost the next generation of visualization technology

Research output: Contribution to journalArticle

30 Citations (Scopus)

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

Fingerprint

Learning systems
Visualization
Learning
Technology
Network security
User interfaces
Feature extraction
Machine Learning

Keywords

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

ASJC Scopus subject areas

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

Cite this

Machine learning to boost the next generation of visualization technology. / Ma, Kwan-Liu.

In: IEEE Computer Graphics and Applications, Vol. 27, No. 5, 01.09.2007, p. 6-9.

Research output: Contribution to journalArticle

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