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» Using Random Forests in the Structured Language Model
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COLING
2010
13 years 3 months ago
Machine Translation with Lattices and Forests
Traditional 1-best translation pipelines suffer a major drawback: the errors of 1best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeli...
Haitao Mi, Liang Huang, Qun Liu
ICASSP
2010
IEEE
13 years 8 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
CVPR
2003
IEEE
14 years 10 months ago
Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field
This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested i...
Sanjiv Kumar, Martial Hebert
LREC
2010
155views Education» more  LREC 2010»
13 years 10 months ago
Efficient Minimal Perfect Hash Language Models
The recent availability of large collections of text such as the Google 1T 5-gram corpus (Brants and Franz, 2006) and the Gigaword corpus of newswire (Graff, 2003) have made it po...
David Guthrie, Mark Hepple, Wei Liu
MICCAI
2009
Springer
14 years 9 months ago
Discriminative, Semantic Segmentation of Brain Tissue in MR Images
A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and ta...
Zhao Yi, Antonio Criminisi, Jamie Shotton, Andr...