In this paper, we investigate the use of the watershed transformation for integrating spatial and spectral information in the process of endmember extraction for spectral unmixing...
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Typically, topology control is perceived as a per-node transmit power control process that achieves certain networklevel objectives. We take an alternative approach of controlling ...
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Subspace-based methods rely on dominant element selection from second order statistics. They have been extended to tensor processing, in particular to tensor data filtering. For t...