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TABLE I NOTATION FOR TREE-STRUCTURED NON-LINEAR MEDIA

in Scalable On-Demand Streaming of Non-Linear Media
by Yanping Zhao, Derek Eager, Mary K. Vernon
Cited by 1

TABLE I NOTATION FOR TREE-STRUCTURED NON-LINEAR MEDIA

in Scalable On-Demand Streaming of Non-Linear
by Media Yanping Zhao, Yanping Zhao, Derek Eager
Cited by 1

TABLE I NOTATION FOR TREE-STRUCTURED NON-LINEAR MEDIA

in Scalable On-Demand Streaming of Non-Linear Media
by Yanping Zhao, Derek Eager, Mary K. Vernon
Cited by 1

TABLE I NOTATION FOR TREE-STRUCTURED NON-LINEAR MEDIA

in Scalable On-Demand Streaming of Non-Linear Media
by Yanping Zhao, Derek Eager
Cited by 1

TABLE I: Notation for Tree-Structured Non-Linear Media

in Scalable On-Demand Streaming of Non-Linear Media
by Yanping Zhao, Derek L. Eager, Mary K. Vernon
Cited by 1

Table 1: Coding results for parallel (A), tree-structured (B), and combination of parallel and tree-structured (C) lter banks.

in On Optimal Tiling Of The Spectrum In Subband Image Compression
by Ilangko Balasingham, Arild Fuldseth, Tor A. Ramstad 1997
"... In PAGE 3: ... To compare the di erent systems apos; performances, im- ages of size 512 512 such as \Lenna quot;, \Barbara quot;, and \Goldhill quot; are tested. Table1 gives the coding per- formance for di erent type of frequency partitioning. Although an adaptive nonuniform FB will be ideal, a combination of parallel and tree-structured system (C) performs fairly well.... ..."
Cited by 3

Table 2 Results Using a Tree Structure

in Study of MPEG-7 Sound Classification and Retrieval
by Hyoung-gook Kim, Edgar Berdahl, Thomas Sikora
"... In PAGE 7: ... That is, the items most similar to a should be at the top of the list and the most dissimilar items at the bottom. The maximum likelihood scores used for classifica- tion are also included in the Table2 , so that the reader can note that calculating the similarity by comparing the state paths and by comparing the maximum likeli- hood scores produce different results. As far as we know, there have not been any tests to show which technique of calculating similarity better corresponds to that of the human hearing system.... ..."

Table 1: Performance measurements for anatomic tree structures

in Visualization of Anatomic Tree Structures with Convolution Surfaces
by S. Oeltze, B. Preim
"... In PAGE 9: ... Figure 16: Visualization of cerebral blood vessels derived from a clinical MR angiography with 149 edges. some results in Table1 . The setup time includes the pre- processing step.... In PAGE 9: ... 15-17. The last line in Table1 represents a complex anatomic tree from a corrosion cast. Due to the size of this model, the Open Inventor optimization failed which explains the low frame rate in the last row.... ..."
Cited by 1

Table 5.1: Results with multi-scale feature extraction on IRMA. Multi-scale Probability model Error

in Local Features for Image Classification
by Tobias Gabriel Benedikt Kölsch

Table 1. Potential hydroelectric energy - Posterior summaries for the parameters Multi-scale model AR(1) model

in A class of multi-scale time series models
by Marco A. R. Ferreira, Mike West, Herbert K. H. Lee, David Higdon 2001
Cited by 2
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