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Conditional random field

Known as: Conditional random fields, Discriminative probabilistic latent variable model 
Conditional random fields (CRFs) are a class of statistical modelling method often applied in pattern recognition and machine learning, where they… (More)
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Topic mentions per year

1992-2017
020040019922017

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.NET FrameworkActivity recognitionBioinformaticsC++
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Broader (1)

Machine learning

Related mentions per year

Related mentions per year

1936-2019
19401960198020002020
Conditional random field
Statistical classification
Machine learning
MATLAB
Java
Computer vision

Papers overview

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Highly Cited
2015
Highly Cited
2015
Conditional Random Fields as Recurrent Neural Networks
Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have… (More)
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Highly Cited
2008
Highly Cited
2008
Efficient, Feature-based, Conditional Random Field Parsing
Discriminative feature-based methods are widely used in natural language processing, but sentence parsing is still dominated by… (More)
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Highly Cited
2007
Highly Cited
2007
Hidden Conditional Random Fields
We present a discriminative latent variable model for classification problems in structured domains where inputs can be… (More)
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Highly Cited
2007
Highly Cited
2007
Learning Conditional Random Fields for Stereo
State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose… (More)
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Highly Cited
2006
Highly Cited
2006
An Improved Chinese Word Segmentation System with Conditional Random Field
In this paper, we describe a Chinese word segmentation system that we developed for the Third SIGHAN Chinese Language Processing… (More)
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Highly Cited
2005
Highly Cited
2005
A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005
We present a Chinese word segmentation system submitted to the closed track of Sighan bakeoff 2005. Our segmenter was built using… (More)
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Highly Cited
2004
Highly Cited
2004
Multiscale conditional random fields for image labeling
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set… (More)
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Highly Cited
2004
Highly Cited
2004
Conditional Random Fields for Object Recognition
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects… (More)
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Highly Cited
2003
Highly Cited
2003
Shallow Parsing with Conditional Random Fields
Conditional random fields for sequence labeling offer advantages over both generative models like HMMs and classifiers applied at… (More)
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Highly Cited
2001
Highly Cited
2001
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields , a framework for building probabilistic models to segment and label sequence data… (More)
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