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CVPR
2007
IEEE
15 years 23 days ago
Online Spatial-temporal Data Fusion for Robust Adaptive Tracking
One problem with the adaptive tracking is that the data that are used to train the new target model often contain errors and these errors will affect the quality of the new target...
Jixu Chen, Qiang Ji
PRICAI
2000
Springer
14 years 2 months ago
Trading Off Granularity against Complexity
The automated prediction of a user's interests and requirements is an area of interest to the Artificial Intelligence community. However, current predictive statistical approa...
Ingrid Zukerman, David W. Albrecht, Ann E. Nichols...
ICMLA
2008
14 years 5 days ago
Probabilistic Exploitation of the Lucas and Kanade Smoothness Constraint
The basic idea of Lucas and Kanade is to constrain the local motion measurement by assuming a constant velocity within a spatial neighborhood. We reformulate this spatial constrai...
Volker Willert, Julian Eggert, Marc Toussaint, Edg...
INTERSPEECH
2010
13 years 5 months ago
Using a DBN to integrate sparse classification and GMM-based ASR
The performance of an HMM-based speech recognizer using MFCCs as input is known to degrade dramatically in noisy conditions. Recently, an exemplar-based noise robust ASR approach,...
Yang Sun, Jort F. Gemmeke, Bert Cranen, Louis ten ...
CISIS
2011
IEEE
12 years 10 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...