101 search results - page 5 / 21 » Fisher Discrimination Dictionary Learning for Sparse Represe... |
MCS
2000
Springer
15 years 1 months ago
2000
Springer
Abstract Investigating a data set of the critical size makes a classification task difficult. Studying dissimilarity data refers to such a problem, since the number of samples equa...
CORR
2010
Springer
14 years 9 months ago
2010
Springer
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
ECCV
2010
Springer
14 years 10 months ago
2010
Springer
Abstract. This paper presents an exemplar-based approach to detecting and localizing human actions, such as running, cycling, and swinging, in realistic videos with dynamic backgro...
101
click to vote
ICASSP
2010
IEEE
14 years 9 months ago
2010
IEEE
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
108
Voted
CVPR
2011
IEEE
14 years 5 months ago
2011
IEEE
Sparse coding, which is the decomposition of a vector using only a few basis elements, is widely used in machine learning and image processing. The basis set, also called dictiona...