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» A Conditional Random Field Model for Video Super-resolution
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AAAI
2008
15 years 2 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam
BMVC
2010
14 years 9 months ago
Motion Coherent Tracking with Multi-label MRF optimization
We present a novel off-line algorithm for target segmentation and tracking in video. In our approach, video data is represented by a multi-label Markov Random Field model, and seg...
David Tsai, Matthew Flagg, James M. Rehg
JMLR
2012
13 years 2 months ago
Sample Complexity of Composite Likelihood
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
Joseph K. Bradley, Carlos Guestrin
ACL
2012
13 years 2 months ago
Learning to Find Translations and Transliterations on the Web
In this paper, we present a new method for learning to finding translations and transliterations on the Web for a given term. The approach involves using a small set of terms and ...
Joseph Z. Chang, Jason S. Chang, Jyh-Shing Roger J...
ICDAR
2011
IEEE
13 years 11 months ago
On-line Handwritten Japanese Characters Recognition Using a MRF Model with Parameter Optimization by CRF
— This paper describes a Markov random field (MRF) model with weighting parameters optimized by conditional random field (CRF) for on-line recognition of handwritten Japanese cha...
Bilan Zhu, Masaki Nakagawa