193 search results - page 1 / 39 » Sparseness Achievement in Hidden Markov Models |
ICIAP
2007
ACM
14 years 5 months ago
2007
ACM
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...
ISBI
2007
IEEE
13 years 11 months ago
2007
IEEE
This paper presents a new framework for shape modeling and analysis. A shape instance is described by a curvature-based shape descriptor. A Profile Hidden Markov Model (PHMM) is ...