Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing th...
Mert R. Sabuncu, B. T. Thomas Yeo, Koen Van Leem...
We present a surprisingly simple system that allows for robust normal reconstruction by dense photometric stereo, in the presence of severe shadows, highlight, transparencies, com...
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Abstract. A parallel Lattice Boltzmann Method (pLBM), which is based on hierarchical spatial decomposition, is designed to perform large-scale flow simulations. The algorithm uses ...
Liu Peng, Ken-ichi Nomura, Takehiro Oyakawa, Rajiv...
In this paper we present a new peer-to-peer (P2P) middleware called CHEap Distributed ARchitecture (Chedar). Chedar is totally decentralized and can be used as a basis for P2P app...
Annemari Auvinen, Mikko Vapa, Matthieu Weber, Niko...