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» Training of Classifiers Using Virtual Samples Only
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ICPR
2004
IEEE
14 years 10 months ago
Tangent Vector Kernels for Invariant Image Classification with SVMs
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
Alexei Pozdnoukhov, Samy Bengio
IGARSS
2009
13 years 6 months ago
A Novel STAP Algorithm using Sparse Recovery Technique
A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...
BMCBI
2010
208views more  BMCBI 2010»
13 years 9 months ago
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...
CIARP
2005
Springer
14 years 2 months ago
Edition Schemes Based on BSE
Edition is an important and useful task in supervised classification specifically for instance-based classifiers because edition discards from the training set those useless or har...
José Arturo Olvera-López, José...
ICPR
2006
IEEE
14 years 10 months ago
Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiogr
One of the most important tasks in medical image analysis is to detect the absence or presence of disease in an image, without having precise delineations of pathology available f...