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» Surface Reconstruction using Learned Shape Models
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PG
2003
IEEE
14 years 2 months ago
Neural Meshes: Statistical Learning Based on Normals
We present a method for the adaptive reconstruction of a surface directly from an unorganized point cloud. The algorithm is based on an incrementally expanding Neural Network and ...
Won-Ki Jeong, Ioannis P. Ivrissimtzis, Hans-Peter ...
MICCAI
2005
Springer
14 years 10 months ago
Parametric Response Surface Models for Analysis of Multi-site fMRI Data
Analyses of fMRI brain data are often based on statistical tests applied to each voxel or use summary statistics within a region of interest (such as mean or peak activation). Thes...
Seyoung Kim, Padhraic Smyth, Hal S. Stern, Jessica...
MICCAI
2004
Springer
14 years 10 months ago
Implicit Active Shape Models for 3D Segmentation in MR Imaging
Extraction of structures of interest in medical images is often an arduous task because of noisy or incomplete data. However, handsegmented data are often available and most of the...
Mikaël Rousson, Nikos Paragios, Rachid Derich...
CVPR
2008
IEEE
14 years 11 months ago
Stereo reconstruction with mixed pixels using adaptive over-segmentation
We present an over-segmentation based, dense stereo algorithm that jointly estimates segmentation and depth. For mixed pixels on segment boundaries, the algorithm computes foregro...
Yuichi Taguchi, Bennett Wilburn, C. Lawrence Zitni...
EMNLP
2010
13 years 7 months ago
A Semi-Supervised Method to Learn and Construct Taxonomies Using the Web
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
Zornitsa Kozareva, Eduard H. Hovy