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NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 6 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
PR
2006
122views more  PR 2006»
15 years 6 months ago
Fast multiscale clustering and manifold identification
We present a novel multiscale clustering algorithm inspired by algebraic multigrid techniques. Our method begins with assembling data points according to local similarities. It us...
Dan Kushnir, Meirav Galun, Achi Brandt
PRL
2006
105views more  PRL 2006»
15 years 6 months ago
Parisian camera placement for vision metrology
This paper presents a novel camera network design methodology based on the Parisian evolutionary computation approach. This methodology proposes to partition the original problem ...
Enrique Dunn, Gustavo Olague, Evelyne Lutton
SIAMSC
2008
237views more  SIAMSC 2008»
15 years 6 months ago
A Variational Shape Optimization Approach for Image Segmentation with a Mumford--Shah Functional
We introduce a novel computational method for a Mumford-Shah functional, which decomposes a given image into smooth regions separated by closed curves. Casting this as a shape opti...
Günay Dogan, Pedro Morin, Ricardo H. Nochetto
IJDAR
2007
77views more  IJDAR 2007»
15 years 6 months ago
Genre as noise: noise in genre
Given a specific information need, documents of the wrong genre can be considered as noise. From this perspective, genre classification helps to separate relevant documents from...
Andrea Stubbe, Christoph Ringlstetter, Klaus U. Sc...