We consider a kernel-based approach to nonlinear classification that coordinates the generation of “synthetic” points (to be used in the kernel) with “chunking” (working wi...
With the increase of the training set’s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel preextracting method f...
Deqiang Han, Chongzhao Han, Yi Yang, Yu Liu, Wenta...
We tackle the problem of automatically classifying cardiac view for an echocardiographic sequence as a multiclass object detection. As a solution, we present an imagebased multicl...
Shaohua Kevin Zhou, J. H. Park, Bogdan Georgescu, ...
Discovering rare categories and classifying new instances of them is
an important data mining issue in many fields, but fully supervised
learning of a rare class classifier is pr...
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...