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» Using Random Forests for Handwritten Digit Recognition
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ICDAR
2009
IEEE
9 years 7 months ago
Recognition of Handwritten Numerical Fields in a Large Single-Writer Historical Collection
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collec...
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb...
IBPRIA
2007
Springer
10 years 1 months ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu
ICPR
2000
IEEE
10 years 1 months ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
ICDAR
2003
IEEE
10 years 2 months ago
A class-modular GLVQ ensemble with outlier learning for handwritten digit recognition
A class-modular generalized learning vector quantization (GLVQ) ensemble method with outlier learning for handwritten digit recognition is proposed. A GLVQ classifier is one of d...
Katsuhiko Takahashi, Daisuke Nishiwaki
ICASSP
2011
IEEE
9 years 1 months ago
Semi-supervised handwritten digit recognition using very few labeled data
We propose a novel semi-supervised classifier for handwritten digit recognition problems that is based on the assumption that any digit can be obtained as a slight transformation...
Steven Van Vaerenbergh, Ignacio Santamaría,...
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