Information Theory Tools for Visualization
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A01=Anton Bardera
A01=Han-Wei Shen
A01=Ivan Viola
A01=Mateu Sbert
A01=Min Chen
A01=Miquel Feixas
Age Group_Uncategorized
Age Group_Uncategorized
AO
AO Map
Author_Anton Bardera
Author_Han-Wei Shen
Author_Ivan Viola
Author_Mateu Sbert
Author_Min Chen
Author_Miquel Feixas
automatic-update
Category1=Non-Fiction
Category=GPF
Children Face Tough Helping Children
computational modelling methods
Conditional Entropy
Conditional Probability Distribution
COP=United States
data analysis techniques
Data Processing Inequality
Delivery_Delivery within 10-20 working days
Entropy Field
Entropy Rate
eq_isMigrated=2
eq_nobargain
Face Tough Helping Children Face
flow visualization
Information Theoretic Measures
information visualization
Issues Issues Issues
Issues Issues Issues Issues Issues
Kullback Leibler Distance
Language_English
Mi
multidimensional data analysis
Normalized Mutual Information
PA=Available
Parallel Coordinates
Price_€100 and above
PS=Active
quantitative visual analytics methods
scientific data interpretation
scientific visualization
Shannon's Information Measures
Shannon’s Information Measures
softlaunch
statistical signal processing
Taylor Diagram
Tough Helping Children Face Tough
Transfer Function Design
uncertainty quantification
Vector Field
Vice Versa
viewpoint metrics
Volume Visualization
Voxel Information
Product details
- ISBN 9781498740937
- Weight: 508g
- Dimensions: 156 x 234mm
- Publication Date: 25 Aug 2016
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
- Language: English
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This book explores Information theory (IT) tools, which have become state of the art to solve and understand better many of the problems in visualization. This book covers all relevant literature up to date. It is the first book solely devoted to this subject, written by leading experts in the field.
Min Chen developed his academic career in Wales between 1984 and 2011. He is currently the professor of scientific visualization at Oxford University and a fellow of Pembroke College. His research interests include visualization, computer graphics and human-computer interaction. His services to the research community include papers co-chair of IEEE Visualization 2007 and 2008, Eurographics 2011, IEEE VAST 2014; co-chair of Volume Graphics 1999 and 2006, EuroVis 2014; associate editor-in-chief of IEEE Transactions on Visualization and Computer Graphics; and co-director of Wales Research Institute of Visual Computing. He is a fellow of British Computer Society, European Computer Graphics Association, and Learned Society of Wales.
Miquel Feixas is an associate professor in Computer Science at the University of Girona. He received an M.Sc. in Theoretical Physics (1979) at the Universitat Autònoma de Barcelona and a Ph.D. in Computer Science (2002) at the Universitat Politècnica de Catalunya. His research is focused on the application of information theory techniques to global illumination, viewpoint selection, image processing, and scientific visualization. He has co-authored two books and more than eighty papers in his areas of research.
Ivan Viola is Assistant Professor at the Vienna University of Technology, Austria and Adjunct Professor at University of Bergen, Norway. He received M.Sc. in 2002 and Ph.D. in 2005 from Vienna University of Technology, Austria. His research is focusing on effective visualization methods that are well understandable by humans. This includes illustrative visualization and perceptually-driven visualization driven by statistical or information theoretic methods.
Anton Bardera is a lecturer in Computer Science at the University of Girona. He received a M.Sc. in Telecommunications engineering (2002) at the Universitat Politècnica de Catalunya and a Ph.D. in Computer Science (2008) at the University of Girona. His research interests include image processing, scientific visualization, information theory, and biomedical applications. He has co-authored one book, 15 journal papers, and many conference papers in his areas of interest.
Han-Wei Shen is a full professor at The Ohio State University. He received his BS degree from Department of Computer Science and Information Engineering at National Taiwan University in 1988, the MS degree in computer science from the State University of New York at Stony Brook in 1992, and the PhD degree in computer science from the University of Utah in 1998. From 1996 to 1999, he was a research scientist at NASA Ames Research Center in Mountain View California. His primary research interests are
