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» The Dark Side of Object Learning: Learning Objects
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CVPR
2009
IEEE
16 years 8 months ago
Real-Time Learning of Accurate Patch Rectification
Recent work [5, 6] showed that learning-based patch rectification methods are both faster and more reliable than affine region methods. Unfortunately, their performance improveme...
Stefan Hinterstoisser, Oliver Kutter, Nassir Navab...
CVPR
2008
IEEE
16 years 6 months ago
The Logistic Random Field - A convenient graphical model for learning parameters for MRF-based labeling
Graphical models are fundamental tools for modeling images and other applications. In this paper, we propose the Logistic Random Field (LRF) model for representing a discrete-valu...
Marshall F. Tappen, Kegan G. G. Samuel, Craig V. D...
ECCV
2008
Springer
16 years 5 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ICPR
2006
IEEE
16 years 5 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum
MICCAI
2004
Springer
16 years 4 months ago
Learning Coupled Prior Shape and Appearance Models for Segmentation
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
Xiaolei Huang, Zhiguo Li, Dimitris N. Metaxas