A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
Curve evolution implementations [3][23] [25] of the Mumford-Shah functional [16] are of broad interest in image segmentation. These implementations, however, have initialization p...
Yongsheng Pan, J. Douglas Birdwell, Seddik M. Djou...
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
We propose a non-linear Canonical Correlation Analysis (CCA) method which works by coordinating or aligning mixtures of linear models. In the same way that CCA extends the idea of...
In this paper, we propose a novel method for rapid feature space Maximum Likelihood Linear Regression (FMLLR) speaker adaptation based on bilinear models. When the amount of adapt...