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条件随机场，应用进行分割和标定序列数据的概率模型.-conditional random fields, a framework for building probabilistic models to segment and label sequence data.
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Many computer vision problems can be formulated
in a Bayesian framework based on Markov Random Fields
(MRF) or Conditional Random Fields (CRF).
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CRFsuite: a fast implementation of Conditional Random Fields (CRFs)
CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possi
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Sign Language Spotting with a Threshold Model
Based on Conditional Random Fields
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In this paper we present Discriminative Random Fields (DRF), a discrim- inative framework for the classification of natural image regions by incor- porating neighborhood spatial dependencies in the labels as well as the observed data. The proposed mo
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This is a Matlab/C++ toolbox of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the high-treewidth setting. Though the code is, in principle, domain independent, I ve developed it wi
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