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JMIV
2006
124views more  JMIV 2006»
15 years 11 days ago
Segmentation of a Vector Field: Dominant Parameter and Shape Optimization
Vector field segmentation methods usually belong to either of three classes: methods which segment regions homogeneous in direction and/or norm, methods which detect discontinuiti...
Tristan Roy, Eric Debreuve, Michel Barlaud, Gilles...
EMNLP
2008
15 years 1 months ago
Lattice-based Minimum Error Rate Training for Statistical Machine Translation
Minimum Error Rate Training (MERT) is an effective means to estimate the feature function weights of a linear model such that an automated evaluation criterion for measuring syste...
Wolfgang Macherey, Franz Josef Och, Ignacio Thayer...
EOR
2007
101views more  EOR 2007»
15 years 11 days ago
Optimizing an objective function under a bivariate probability model
The motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probabi...
Xavier Brusset, Nico M. Temme
92
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ICCV
2001
IEEE
16 years 2 months ago
Reconstructing Surfaces Using Anisotropic Basis Functions
Point sets obtained from computer vision techniques are often noisy and non-uniform. We present a new method of surface reconstruction that can handle such data sets using anisotr...
Huong Quynh Dinh, Greg Turk, Gregory G. Slabaugh
113
Voted
TNN
2010
176views Management» more  TNN 2010»
14 years 7 months ago
On the weight convergence of Elman networks
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...
Qing Song