We present a general, simple feature representation of sequences that allows efficient inexact matching, comparison and classification of sequential data. This approach, recently ...
In this paper, we propose a new feature extraction method, which is robust against rotation and histogram equalization for texture classification. To this end, we introduce the co...
In this paper, we present a kernel-based approach to the clustering of diffusion tensors and fiber tracts. We propose to use a Mercer kernel over the tensor space where both spati...
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...