This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
In earlier work, we proposed treating wide baseline matching of feature points as a classification problem, in which each class corresponds to the set of all possible views of suc...
The thresholded t-map produced by the General Linear Model (GLM) gives an effective summary of activation patterns in functional brain images and is widely used for feature selecti...
Abstract. We perform discriminative analysis of brain structures using morphometric information. Spherical harmonics technique and point distribution model are used for shape descr...
Li Shen, James Ford, Fillia Makedon, Yuhang Wang, ...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...