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NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 6 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
FSKD
2008
Springer
120views Fuzzy Logic» more  FSKD 2008»
13 years 7 months ago
An Unsupervised Gaussian Mixture Classification Mechanism Based on Statistical Learning Analysis
This paper presents a scheme for unsupervised classification with Gaussian mixture models by means of statistical learning analysis. A Bayesian Ying-Yang harmony learning system a...
Rui Nian, Guangrong Ji, Michel Verleysen
ACCV
2009
Springer
14 years 27 days ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
ICIAR
2010
Springer
13 years 3 months ago
Image Segmentation for Robots: Fast Self-adapting Gaussian Mixture Model
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
Nicola Greggio, Alexandre Bernardino, José ...
ICDAR
2009
IEEE
14 years 1 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia