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» Conditional Random Fields for Multi-Camera Object Detection
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CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Segmentation of Objects using Efficient Learning
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
NIPS
2008
13 years 9 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
ACL
2006
13 years 9 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
ACL
2004
13 years 9 months ago
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding ...
Michelle L. Gregory, Yasemin Altun
INTERSPEECH
2010
13 years 2 months ago
SCARF: a segmental conditional random field toolkit for speech recognition
This paper describes a new toolkit - SCARF - for doing speech recognition with segmental conditional random fields. It is designed to allow for the integration of numerous, possib...
Geoffrey Zweig, Patrick Nguyen