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CVPR
2005
IEEE
16 years 8 months ago
WaldBoost - Learning for Time Constrained Sequential Detection
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Jan Sochman, Jiri Matas
AVSS
2005
IEEE
16 years 8 days ago
Denoising image sequences does not require motion estimation
State of the art movie restoration methods either estimate motion and filter out the trajectories, or compensate the motion by an optical flow estimate and then filter out the ...
Antoni Buades, Bartomeu Coll, Jean-Michel Morel
BMCBI
2005
99views more  BMCBI 2005»
15 years 6 months ago
Effective ambiguity checking in biosequence analysis
Background: Ambiguity is a problem in biosequence analysis that arises in various analysis tasks solved via dynamic programming, and in particular, in the modeling of families of ...
Janina Reeder, Peter Steffen, Robert Giegerich
ICIP
1998
IEEE
16 years 8 months ago
Reducing the Computational Complexity of a Map Post-Processing Algorithm for Video Sequences
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
Mark A. Robertson, Robert L. Stevenson
172
Voted
PKDD
2009
Springer
181views Data Mining» more  PKDD 2009»
16 years 1 months ago
Active Learning for Reward Estimation in Inverse Reinforcement Learning
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Manuel Lopes, Francisco S. Melo, Luis Montesano