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» A Framework for Multiple-Instance Learning
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JAIR
1998
198views more  JAIR 1998»
15 years 6 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
ISVC
2010
Springer
15 years 5 months ago
Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...
Scott Spurlock, Remco Chang, Xiaoyu Wang, George A...
DIS
2010
Springer
15 years 4 months ago
Concept Convergence in Empirical Domains
How to achieve shared meaning is a significant issue when more than one intelligent agent is involved in the same domain. We define the task of concept convergence, by which intell...
Santiago Ontañón, Enric Plaza
CVPR
2010
IEEE
16 years 2 months ago
Spatialized Epitome and Its Applications
Due to the lack of explicit spatial consideration, existing epitome model may fail for image recognition and target detection, which directly motivates us to propose the so-calle...
Xinqi Chu, Shuicheng Yan, Liyuan Li, Kap Luk Chan,...
CVPR
2012
IEEE
13 years 9 months ago
3D landmark model discovery from a registered set of organic shapes
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...
Clement Creusot, Nick Pears, Jim Austin