Partitioning a large set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means algorithm is best suited for implementing this operation becau...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
In this paper, we present a novel algorithm for non-rigidly registering two high angular resolution diffusion weighted MRIs (HARDI), each represented by a Gaussian mixture field (G...
Baba C. Vemuri, Guang Cheng 0002, Paul R. Carney, ...
In this article we address the issue of denoising photon-limited image data by deriving new and efficient multivariate Bayesian estimators that approximate the conditional expecta...
Spectral mixture analysis is an important task for remotely sensed hyperspectral data interpretation. In spectral unmixing, both the determination of spectrally pure signatures (e...