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ACL
2008
13 years 8 months ago
Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums
Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not on...
Shilin Ding, Gao Cong, Chin-Yew Lin, Xiaoyan Zhu
AVSS
2006
IEEE
14 years 24 days ago
A Random Field Model for Improved Feature Extraction and Tracking
This paper presents a novel method for illuminationinvariant and contrast preserving feature extraction, aimed at improving performance of tracking under complex light condition. ...
Xiaotong Yuan, Stan Z. Li
ICIP
2009
IEEE
14 years 6 months ago
A Markov Random Field Model for Extracting Near-Circular Shapes
We propose a binary Markov Random Field (MRF) model that assigns high probability to regions in the image domain consisting of an unknown number of circles of a given radius. We...
Tamas Blaskovics, Zoltan Kato, and Ian Jermyn
NIPS
2004
13 years 8 months ago
Semi-Markov Conditional Random Fields for Information Extraction
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...
Sunita Sarawagi, William W. Cohen
ICIP
2002
IEEE
14 years 8 months ago
Extract highlights from baseball game video with hidden Markov models
In this paper, we describe a statistical method to detect highlights in a baseball game video. The input video is first segmented into scene shots, within which the camera motion ...
Peng Chang, Mei Han, Yihong Gong