Abstract--Boosting covariance data on Riemannian manifolds has proven to be a convenient strategy in a pedestrian detection context. In this paper we show that the detection perfor...
Diego Tosato, Michela Farenzena, Marco Cristani, V...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
Abstract-- Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to databa...
This paper is devoted to the registration of gene expression data to a neuroanatomical mouse atlas in two dimensions. We use a nonlinear elasticity regularization allowing large d...
Tungyou Lin, Erh-Fang Lee, Ivo D. Dinov, Carole Le...