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» Discriminative learned dictionaries for local image analysis
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ICIP
2006
IEEE
16 years 8 months ago
Local Discriminant Embedding with Tensor Representation
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Jian Xia, Dit-Yan Yeung, Guang Dai
CIVR
2007
Springer
166views Image Analysis» more  CIVR 2007»
16 years 24 days ago
Multi-level local descriptor quantization for bag-of-visterms image representation
In the past, quantized local descriptors have been shown to be a good base for the representation of images, that can be applied to a wide range of tasks. However, current approac...
Pedro Quelhas, Jean-Marc Odobez
AAAI
2012
13 years 9 months ago
Multi-Label Learning by Exploiting Label Correlations Locally
It is well known that exploiting label correlations is important for multi-label learning. Existing approaches typically exploit label correlations globally, by assuming that the ...
Sheng-Jun Huang, Zhi-Hua Zhou
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
MM
2006
ACM
203views Multimedia» more  MM 2006»
16 years 18 days ago
Learning image manifolds by semantic subspace projection
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Jie Yu, Qi Tian