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BMCBI
2007
178views more  BMCBI 2007»
14 years 11 months ago
SVM clustering
Background: Support Vector Machines (SVMs) provide a powerful method for classification (supervised learning). Use of SVMs for clustering (unsupervised learning) is now being cons...
Stephen Winters-Hilt, Sam Merat
113
Voted
ACCV
2010
Springer
14 years 6 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan
113
Voted
CORR
2004
Springer
144views Education» more  CORR 2004»
14 years 11 months ago
The Google Similarity Distance
Words and phrases acquire meaning from the way they are used in society, from their relative semantics to other words and phrases. For computers the equivalent of `society' is...
Rudi Cilibrasi, Paul M. B. Vitányi
94
Voted
VIP
2003
15 years 1 months ago
Optimal Selection of Image Segmentation Algorithms Based on Performance Prediction
Using different algorithms to segment different images is a quite straightforward strategy for automated image segmentation. But the difficulty of the optimal algorithm selection ...
Yong Xia, David Dagan Feng, Rongchun Zhao
BMCBI
2006
146views more  BMCBI 2006»
14 years 11 months ago
Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE
Background: In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease...
Satoshi Niijima, Satoru Kuhara