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ICIP
2004
IEEE
16 years 6 months ago
Sparse representation of images with hybrid linear models
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
Kun Huang, Allen Y. Yang, Yi Ma
135
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ICPR
2006
IEEE
16 years 6 months ago
ICA-Based Clustering for Resolving Permutation Ambiguity in Frequency-Domain Convolutive Source Separation
Permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. In this pape...
Minje Kim, Seungjin Choi
ICPR
2004
IEEE
16 years 6 months ago
Relevant Linear Feature Extraction Using Side-information and Unlabeled Data
"Learning with side-information" is attracting more and more attention in machine learning problems. In this paper, we propose a general iterative framework for relevant...
Changshui Zhang, Fei Wu, Yonglei Zhou
IJCNN
2007
IEEE
15 years 11 months ago
FEBAM: A Feature-Extracting Bidirectional Associative Memory
—In this paper, a new model that can ultimately create its own set of perceptual features is proposed. Using a bidirectional associative memory (BAM)-inspired architecture, the r...
Sylvain Chartier, Gyslain Giguère, Patrice ...
ICMCS
2005
IEEE
138views Multimedia» more  ICMCS 2005»
15 years 10 months ago
Overcomplete ICA-based Manmade Scene Classification
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
Matthew Boutell, Jiebo Luo