Feature detection on MR images has largely relied on intensity classification and gradient-based magnitudes. In this paper, we propose the use of phase congruency as a more robust ...
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
In this paper we present a novel scheme for unstructured audio scene classification that possesses three highly desirable and powerful features: autonomy, scalability, and robust...
Julian Ramos, Sajid M. Siddiqi, Artur Dubrawski, G...
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...