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DAGM
2007
Springer
14 years 17 days ago
Greedy-Based Design of Sparse Two-Stage SVMs for Fast Classification
Cascades of classifiers constitute an important architecture for fast object detection. While boosting of simple (weak) classifiers provides an established framework, the design of...
Rezaul Karim, Martin Bergtholdt, Jörg H. Kapp...
EMNLP
2008
13 years 10 months ago
Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks
We present a graph-based semi-supervised label propagation algorithm for acquiring opendomain labeled classes and their instances from a combination of unstructured and structured...
Partha Pratim Talukdar, Joseph Reisinger, Marius P...
ICCV
2007
IEEE
14 years 10 months ago
Boosting Invariance and Efficiency in Supervised Learning
In this paper we present a novel boosting algorithm for supervised learning that incorporates invariance to data transformations and has high generalization capabilities. While on...
Andrea Vedaldi, Paolo Favaro, Enrico Grisan
ICDAR
2009
IEEE
13 years 6 months ago
Combining Multiple HMMs Using On-line and Off-line Features for Off-line Arabic Handwriting Recognition
This paper presents an off-line Arabic Handwriting recognition system based on the selection of different state of the art features and the combination of multiple Hidden Markov M...
Mahdi Hamdani, Haikal El Abed, Monji Kherallah, Ad...
FUIN
2002
132views more  FUIN 2002»
13 years 8 months ago
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
Grzegorz Góra, Arkadiusz Wojna