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146
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PR
2006
147views more  PR 2006»
15 years 3 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung
136
Voted
TNN
1998
146views more  TNN 1998»
15 years 3 months ago
An analytical framework for local feedforward networks
Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are refer...
S. Weaver, L. Baird, Marios M. Polycarpou
ICPR
2006
IEEE
16 years 4 months ago
Object Localization Using Input/Output Recursive Neural Networks
Localizing objects in images is a difficult task and represents the first step to the solution of the object recognition problem. This paper presents a novel approach to the local...
Lorenzo Sarti, Marco Maggini, Monica Bianchini
125
Voted
DAGM
2007
Springer
15 years 10 months ago
Image Statistics and Local Spatial Conditions for Nonstationary Blurred Image Reconstruction
Deblurring is important in many visual systems. This paper presents a novel approach for nonstationary blurred image reconstruction with ringing reduction in a variational Bayesian...
Hongwei Zheng, Olaf Hellwich
131
Voted
ICRA
2002
IEEE
110views Robotics» more  ICRA 2002»
15 years 8 months ago
Mobile Robot Localization using an Incremental Eigenspace Model
— When using appearance-based recognition for self-localization of mobile robots, the images obtained during the exploration of the environment need to be efficiently stored in t...
Matej Artac, Matjaz Jogan, Ales Leonardis