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» Discriminative learned dictionaries for local image analysis
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ICIP
2006
IEEE
15 years 11 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»
15 years 3 months 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
12 years 12 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 2 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»
15 years 3 months 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