75 search results - page 12 / 15 » Sparse Feature Learning for Deep Belief Networks |
CVPR
2010
IEEE
15 years 6 months ago
2010
IEEE
In this paper, we propose a novel supervised hierarchical sparse coding model based on local image descriptors for classification tasks. The supervised dictionary training is perf...
JMLR
2010
14 years 4 months ago
2010
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
71
Voted
ICANN
2009
Springer
15 years 2 months ago
2009
Springer
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
JMLR
2006
14 years 9 months ago
2006
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
90
Voted
EMMCVPR
2005
Springer
15 years 3 months ago
2005
Springer
This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...