193 search results - page 14 / 39 » Sparseness Achievement in Hidden Markov Models |
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Abstract. Natural scenes consist of a wide variety of stochastic patterns. While many patterns are represented well by statistical models in two dimensional regions as most image s...
ICIP
2008
IEEE
14 years 9 months ago
2008
IEEE
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Exemplar-based techniques, such as k-nearest neighbors (kNNs) and Sparse Representations (SRs), can be used to model a test sample from a few training points in a dictionary set. ...
COLING
1996
13 years 9 months ago
1996
In this paper, we describe a new model for word alignment in statistical translation and present experimental results. The idea of the model is to make the alignment probabilities...
NIPS
2008
13 years 9 months ago
2008
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...