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» Learning Models for Predicting Recognition Performance
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RECOMB
2005
Springer
15 years 10 months ago
Predicting Protein-Peptide Binding Affinity by Learning Peptide-Peptide Distance Functions
Many important cellular response mechanisms are activated when a peptide binds to an appropriate receptor. In the immune system, the recognition of pathogen peptides begins when th...
Chen Yanover, Tomer Hertz
84
Voted
CVPR
2003
IEEE
15 years 11 months ago
A Bayesian Framework for Fusing Multiple Word Knowledge Models in Videotext Recognition
Videotext recognition is challenging due to low resolution, diverse fonts/styles, and cluttered background. Past methods enhanced recognition by using multiple frame averaging, im...
DongQing Zhang, Shih-Fu Chang
UM
2007
Springer
15 years 3 months ago
Inducing User Affect Recognition Models for Task-Oriented Environments
Accurately recognizing users’ affective states could contribute to more productive and enjoyable interactions, particularly for task-oriented learning environments. In addition t...
Sunyoung Lee, Scott W. McQuiggan, James C. Lester
ICML
1990
IEEE
15 years 1 months ago
Average Case Analysis of Conjunctive Learning Algorithms
We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the...
Michael J. Pazzani, Wendy Sarrett
ICMCS
2005
IEEE
90views Multimedia» more  ICMCS 2005»
15 years 3 months ago
Integrating co-training and recognition for text detection
Training a good text detector requires a large amount of labeled data, which can be very expensive to obtain. Cotraining has been shown to be a powerful semi-supervised learning t...
Wen Wu, Datong Chen, Jie Yang