565 search results - page 23 / 113 » Denoising and recognition using hidden Markov models with ob... |
HICSS
2003
IEEE
14 years 1 months ago
2003
IEEE
This paper describes a novel approach using Hidden Markov Models (HMM) to detect complex Internet attacks. These attacks consist of several steps that may occur over an extended pe...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveilla...
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
SSPR
2010
Springer
13 years 6 months ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...