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TNN
2008
82views more  TNN 2008»
14 years 11 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...
JCB
2007
146views more  JCB 2007»
14 years 11 months ago
MSOAR: A High-Throughput Ortholog Assignment System Based on Genome Rearrangement
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics, since many computational methods for solving variou...
Zheng Fu, Xin Chen, Vladimir Vacic, Peng Nan, Yang...
ICCV
2003
IEEE
16 years 29 days ago
An affine invariant deformable shape representation for general curves
Automatic construction of Shape Models from examples has been the focus of intense research during the last couple of years. These methods have proved to be useful for shape segme...
Anders Ericsson, Kalle Åström
82
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ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
15 years 4 months ago
Combining Multiple Weak Clusterings
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...
CVPR
2007
IEEE
16 years 1 months ago
Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration
We present a parameter free approach that utilizes multiple cues for image segmentation. Beginning with an image, we execute a sequence of bottom-up aggregation steps in which pix...
Sharon Alpert, Meirav Galun, Ronen Basri, Achi Bra...