Abstract--This paper deals with the reconstruction of T1-T2 correlation spectra in nuclear magnetic resonance relaxometry. The ill-posed character and the large size of this invers...
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
We present a novel, efficient, initializationfree approach to the problem of epipolar geometry estimation, by formulating it as one of hyperplane inference from a sparse and noisy...