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BMCBI
2004
208views more  BMCBI 2004»
15 years 4 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
CGF
2002
184views more  CGF 2002»
15 years 4 months ago
The 3D Model Acquisition Pipeline
Three-dimensional (3D) image acquisition systems are rapidly becoming more affordable, especially systems based on commodity electronic cameras. At the same time, personal compute...
Fausto Bernardini, Holly E. Rushmeier
CGA
1998
15 years 4 months ago
Principles for Information Visualization Spreadsheets
ns, with large, abstract, multidimensional data sets that are visually represented in multiple ways. We illustrate how spreadsheet techniques provide a structured, intuitive, and p...
Ed Huai-hsin Chi, John Riedl, Phillip Barry, Josep...
SAC
2002
ACM
15 years 3 months ago
Decision tree classification of spatial data streams using Peano Count Trees
Many organizations have large quantities of spatial data collected in various application areas, including remote sensing, geographical information systems (GIS), astronomy, compu...
Qiang Ding, Qin Ding, William Perrizo
PVLDB
2008
116views more  PVLDB 2008»
15 years 3 months ago
Tighter estimation using bottom k sketches
Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a ...
Edith Cohen, Haim Kaplan
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