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» Using Random Forests for Handwritten Digit Recognition
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NIPS
2004
13 years 6 months ago
Using Random Forests in the Structured Language Model
In this paper, we explore the use of Random Forests (RFs) in the structured language model (SLM), which uses rich syntactic information in predicting the next word based on words ...
Peng Xu, Frederick Jelinek
MCS
2007
Springer
13 years 11 months ago
An Experimental Study on Rotation Forest Ensembles
Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...
Ludmila I. Kuncheva, Juan José Rodrí...
PREMI
2005
Springer
13 years 10 months ago
Eliciting Domain Knowledge in Handwritten Digit Recognition
Pattern recognition methods for complex structured objects such as handwritten characters often have to deal with vast search spaces. Developed techniques, despite significant adv...
Tuan Trung Nguyen
CVPR
2006
IEEE
14 years 7 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...
ICPR
2002
IEEE
14 years 6 months ago
A String Length Predictor to Control the Level Building of HMMs for Handwritten Numeral Recognition
In this paper a two-stage HMM-based method for recognizing handwritten numeral strings is extended to work with handwritten numeral strings of unknown length. We have proposed a B...
Alceu de Souza Britto Jr., Ching Y. Suen, Fl&aacut...