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BMCBI
2011
8 years 4 months ago
Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
Background: Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture th...
Bailing Zhang, Tuan D. Pham
ICPR
2010
IEEE
8 years 8 months ago
Multi-class Graph Boosting with Subgraph Sharing for Object Recognition
In this paper, we propose a novel multi-class graph boosting algorithm to recognize different visual objects. The proposed method treats subgraph as feature to construct base clas...
Bang Zhang, Getian Ye, Yang Wang 0002, Wei Wang, J...
PAMI
2008
155views more  PAMI 2008»
8 years 9 months ago
Subclass Problem-Dependent Design for Error-Correcting Output Codes
A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word fo...
Sergio Escalera, David M. J. Tax, Oriol Pujol, Pet...
IJCAI
2003
8 years 11 months ago
Constructing Diverse Classifier Ensembles using Artificial Training Examples
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
Prem Melville, Raymond J. Mooney
CIARP
2008
Springer
9 years 9 days ago
Ensemble Approaches to Facial Action Unit Classification
Facial action unit (au) classification is an approach to face expression recognition that decouples the recognition of expression from individual actions. In this paper, upper face...
Terry Windeatt, Kaushala Dias
MCS
2000
Springer
9 years 1 months ago
Classifier Instability and Partitioning
Various methods exist for reducing correlation between classifiers in a multiple classifier framework. The expectation is that the composite classifier will exhibit improved perfor...
Terry Windeatt
AUSAI
2006
Springer
9 years 2 months ago
Virtual Attribute Subsetting
Attribute subsetting is a meta-classification technique, based on learning multiple base-level classifiers on projections of the training data. In prior work with nearest-neighbour...
Michael Horton, R. Mike Cameron-Jones, Raymond Wil...
ICMCS
2006
IEEE
151views Multimedia» more  ICMCS 2006»
9 years 4 months ago
Support Vector Machine for Multiple Feature Classifcation
In this paper an effective method of using SVM classifier for multiple feature classification is proposed. Compared with traditional combination methods where all needed base clas...
Bing-Yu Sun, Moon-Chuen Lee
CIKM
2007
Springer
9 years 4 months ago
A novel scheme for domain-transfer problem in the context of sentiment analysis
In this work, we attempt to tackle domain-transfer problem by combining old-domain labeled examples with new-domain unlabeled ones. The basic idea is to use old-domain-trained cla...
Songbo Tan, Gaowei Wu, Huifeng Tang, Xueqi Cheng
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