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» Learning from Multiple Sources of Inaccurate Data
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VCIP
2003
147views Communications» more  VCIP 2003»
13 years 10 months ago
An objective method for combining multiple subjective data sets
International recommendations for subjective video quality assessment (e.g., ITU-R BT.500-11) include specifications for how to perform many different types of subjective tests. I...
Margaret H. Pinson, Stephen Wolf
ICDE
2003
IEEE
159views Database» more  ICDE 2003»
14 years 10 months ago
Scaling up the ALIAS Duplicate Elimination System
Duplicate elimination is an important stage in integrating data from multiple sources. The challenges involved are finding a robust deduplication function that can identify when t...
Sunita Sarawagi, Alok Kirpal
CLEAR
2007
Springer
120views Biometrics» more  CLEAR 2007»
14 years 3 months ago
TUT Acoustic Source Tracking System 2007
Abstract. This paper is a documentation of the acoustic person tracking system developed by TUT. The system performance was evaluated in the CLEAR 2007 evaluation. The proposed sys...
Teemu Korhonen, Pasi Pertilä
WACV
2005
IEEE
14 years 2 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
KDD
2009
ACM
190views Data Mining» more  KDD 2009»
14 years 9 months ago
Named entity mining from click-through data using weakly supervised latent dirichlet allocation
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
Gu Xu, Shuang-Hong Yang, Hang Li