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AAAI
2011
12 years 9 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
AAAI
2004
13 years 10 months ago
Rapid Object Recognition from Discriminative Regions of Interest
Object recognition and detection represent a relevant component in cognitive computer vision systems, such as in robot vision, intelligent video surveillance systems, or multi-mod...
Gerald Fritz, Christin Seifert, Lucas Paletta, Hor...
SCALESPACE
2007
Springer
14 years 3 months ago
Towards Segmentation Based on a Shape Prior Manifold
Incorporating shape priors in image segmentation has become a key problem in computer vision. Most existing work is limited to a linearized shape space with small deformation modes...
Patrick Etyngier, Renaud Keriven, Jean-Philippe Po...
CVPR
2006
IEEE
14 years 11 months ago
Graph Laplacian Kernels for Object Classification from a Single Example
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Hong Chang, Dit-Yan Yeung
HIS
2007
13 years 10 months ago
Active Selection of Training Examples for Meta-Learning
Meta-Learning has been used to relate the performance of algorithms and the features of the problems being tackled. The knowledge in Meta-Learning is acquired from a set of meta-e...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...