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» Learning to Classify X-Ray Images Using Relational Learning
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CVPR
2008
IEEE
14 years 10 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
NECO
2010
154views more  NECO 2010»
13 years 7 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 9 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
CVPR
2007
IEEE
14 years 3 months ago
Unsupervised Learning of Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen