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CVPR
2010
IEEE
15 years 6 months ago
Hierarchical Convolutional Sparse Image Decomposition
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew Zeiler, Dilip Krishnan, Graham Taylor, Rob...
CVPR
2010
IEEE
1192views Computer Vision» more  CVPR 2010»
15 years 6 months ago
RASL: Robust Alignment by Sparse and Low-rank Decomposition for Linearly Correlated Images
This paper studies the problem of simultaneously aligning a batch of linearly correlated images despite gross corruption (such as occlusion). Our method seeks an optimal set of im...
Yigang Peng, Arvind Balasubramanian, John Wright, ...
ICASSP
2009
IEEE
15 years 5 months ago
Sparse decomposition of mixed audio signals by basis pursuit with autoregressive models
We develop a framework to detect when certain sounds are present in a mixed audio signal. We focus on the regime where out of a large number of possible sounds, a small but unknow...
Youngmin Cho, Lawrence K. Saul
IDA
2009
Springer
15 years 4 months ago
Extension of Sparse, Adaptive Signal Decompositions to Semi-blind Audio Source Separation
Abstract. We apply sparse, fast and flexible adaptive lapped orthogonal transforms to underdetermined audio source separation using the time-frequency masking framework. This norm...
Andrew Nesbit, Emmanuel Vincent, Mark D. Plumbley
76
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ICASSP
2010
IEEE
14 years 10 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...