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BMCBI
2007
178views more  BMCBI 2007»
13 years 9 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
JBI
2007
148views Bioinformatics» more  JBI 2007»
13 years 9 months ago
A method for linking computed image features to histological semantics in neuropathology
In medical image analysis, the image content is often represented by computed features that need to be interpreted at a clinical level of understanding to support lopment of clini...
Birgit Lessmann, Tim W. Nattkemper, V. H. Hans, An...
ICML
2008
IEEE
14 years 10 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
MM
2005
ACM
172views Multimedia» more  MM 2005»
14 years 2 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
ICASSP
2011
IEEE
13 years 26 days ago
A new method for visual stylometry on impressionist paintings
A new emerging field, that of visual stylometry of art, proposes to apply image analysis and machine learning tools to high-resolution digital images of artwork in order to assis...
Hanchao Qi, Shannon Hughes