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» Using feature models to automate model transformations
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SSDBM
2003
IEEE
160views Database» more  SSDBM 2003»
16 years 15 hour ago
The Virtual Data Grid: A New Model and Architecture for Data-Intensive Collaboration
It is now common to encounter communities engaged in the collaborative analysis and transformation of large quantities of data over extended time periods. We argue that these comm...
Ian T. Foster
CVPR
2005
IEEE
16 years 8 months ago
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
We combine local texture features (PCA-SIFT), global features (shape context), and spatial features within a single multi-layer AdaBoost model of object class recognition. The fir...
Wei Zhang 0002, Bing Yu, Gregory J. Zelinsky, Dimi...
ECMDAFA
2009
Springer
138views Hardware» more  ECMDAFA 2009»
16 years 1 months ago
A Pattern Mining Approach Using QVT
Model Driven Software Development (MDSD) has matured over the last few years and is now becoming an established technology. Models are used in various contexts, where the possibili...
Jens Kübler, Thomas Goldschmidt
ICMCS
2006
IEEE
112views Multimedia» more  ICMCS 2006»
16 years 24 days ago
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
The Feature Vector approach is one of the most popular schemes for managing multimedia data. For many data types such as audio, images, or 3D models, an abundance of different Fea...
Tobias Schreck, Daniel A. Keim, Christian Panse
ICMLA
2007
15 years 8 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...