Issue No. 05 - September/October (2007 vol. 27)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2007.129
Kwan-Liu Ma , University of California at Davis
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.
information visualization, intelligent systems, interface design, machine learning, scientific visualization
K. Ma, "Machine Learning to Boost the Next Generation of Visualization Technology," in IEEE Computer Graphics and Applications, vol. 27, no. , pp. 6-9, 2007.