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» Soft Failure Detection Using Factorial Hidden Markov Models
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ICMLA
2007
13 years 6 months ago
Soft Failure Detection Using Factorial Hidden Markov Models
In modern business, educational, and other settings, it is common to provide a digital network that interconnects hardware devices for shared access by the users (e.g., in an of...
Guillaume Bouchard, Jean-Marc Andreoli
ICASSP
2011
IEEE
12 years 8 months ago
Gain-robust multi-pitch tracking using sparse nonnegative matrix factorization
While nonnegative matrix factorization (NMF) has successfully been applied for gain-robust multi-pitch detection, a method to track pitch values over time was not provided. We emb...
Robert Peharz, Michael Wohlmayr, Franz Pernkopf
ICMCS
2000
IEEE
138views Multimedia» more  ICMCS 2000»
13 years 9 months ago
Event-Coupled Hidden Markov Models
Inferences from time-series data can be greatly enhanced by taking into account multiple modalities. In some cases, such as audio of speech and the corresponding video of lip gest...
Trausti T. Kristjansson, Brendan J. Frey, Thomas S...
ICCV
2003
IEEE
13 years 9 months ago
Markov-Based Failure Prediction for Human Motion Analysis
This paper presents a new method of detecting and predicting motion tracking failures with applications in human motion and gait analysis. We define a tracking failure as an event...
Shiloh L. Dockstader, Nikita S. Imennov, A. Murat ...
JAIHC
2010
205views more  JAIHC 2010»
13 years 3 months ago
Soft computing in intrusion detection: the state of the art
The state of the art is explored in using soft computing (SC) methods for network intrusion detection, including the examination of efforts in ten specific areas of SC as well as ...
Chet Langin, Shahram Rahimi