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» A Framework for Machine Learning with Ambiguous Objects
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CVPR
2012
IEEE
11 years 8 months ago
The Shape Boltzmann Machine: A strong model of object shape
A good model of object shape is essential in applications such as segmentation, object detection, inpainting and graphics. For example, when performing segmentation, local constra...
S. M. Ali Eslami, Nicolas Heess, John M. Winn
ICALT
2006
IEEE
13 years 11 months ago
Metadata Challenges for Situational Properties of Learning Objects
raction of free-standing metadata describing learning objects is typified by an analytical model which primarily focuses on the encoding of discrete properties pertaining to the ...
Baden Hughes, Roderick A. Farmer
ICALT
2006
IEEE
13 years 11 months ago
Towards Effective Usage-Based Learning Applications: Track and Learn from User Experience(s)
In this paper we propose a schema and framework for recording and managing attention metadata. This framework is intended to capture, manage, and re-use data about attention users...
Jehad Najjar, Erik Duval, Martin Wolpers
ICCV
2007
IEEE
14 years 7 months ago
Objects in Context
In the task of visual object categorization, semantic context can play the very important role of reducing ambiguity in objects' visual appearance. In this work we propose to...
Andrew Rabinovich, Andrea Vedaldi, Carolina Galleg...
ICML
2009
IEEE
14 years 6 months ago
Learning non-redundant codebooks for classifying complex objects
Codebook-based representations are widely employed in the classification of complex objects such as images and documents. Most previous codebook-based methods construct a single c...
Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Di...