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» Application of Level Set Methods in Computer Vision
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ICPR
2008
IEEE
14 years 11 months ago
Collaborative learning by boosting in distributed environments
In this paper we propose a new distributed learning method called distributed network boosting (DNB) algorithm for distributed applications. The learned hypotheses are exchanged b...
Shijun Wang, Changshui Zhang
ICIC
2005
Springer
14 years 3 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao
ICPR
2004
IEEE
14 years 11 months ago
Attribute Relevance in Multiclass Data Sets Using the Naive Bayes Rule
Feature selection using the naive Bayes rule is presented for the case of multiclass data sets. In this paper, the EM algorithm is applied to each class projected over the feature...
José Martínez Sotoca, José Sa...
ICPR
2008
IEEE
14 years 4 months ago
Active contour algorithm for texture segmentation using a texture feature set
This paper presents a novel algorithm for unsupervised texture segmentation. We incorporate a set of texture features under a segmentation framework, based on the active contour w...
Sandro Vega-Pons, José Luís Gil Rodr...
CBMS
2006
IEEE
14 years 4 months ago
Efficient Rotation Invariant Retrieval of Shapes with Applications in Medical Databases
Recognition of shapes in images is an important problem in computer vision with application in various medical problems, including robotic surgery and cell analysis. The similarit...
Selina Chu, Shrikanth S. Narayanan, C. C. Jay Kuo