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ER
1995
Springer
152views Database» more  ER 1995»
15 years 1 months ago
A Logic Framework for a Semantics of Object-Oriented Data Modeling
We describe a (meta) formalism for defining a variety of (object oriented) data models in a unified framework based on a variation of first-order logic. As specific example we use...
Olga De Troyer, Robert Meersman
UAI
2004
14 years 11 months ago
Recovering Articulated Object Models from 3D Range Data
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang,...
JSC
2006
102views more  JSC 2006»
14 years 10 months ago
Counting and locating the solutions of polynomial systems of maximum likelihood equations, I
In statistics, mixture models consisting of several component subpopulations are used widely to model data drawn from heterogeneous sources. In this paper, we consider maximum lik...
Max-Louis G. Buot, Donald St. P. Richards
CVPR
2011
IEEE
14 years 6 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
ICMCS
1995
IEEE
156views Multimedia» more  ICMCS 1995»
15 years 1 months ago
Spatio-Temporal Modeling of Video Data for On-Line Object-Oriented Query Processing
This paper presents a framework for data modeling ntic abstraction of image/video data. The framework is based on spatio-temporalinformation associated with salient objects in an ...
Young Francis Day, Serhan Dagtas, Mitsutoshi Iino,...