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» An Optimal Algorithm for the Maximum-Density Segment Problem
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AAAI
1998
13 years 8 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge
ICDM
2006
IEEE
116views Data Mining» more  ICDM 2006»
14 years 1 months ago
Improving Personalization Solutions through Optimal Segmentation of Customer Bases
On the Web, where the search costs are low and the competition is just a mouse click away, it is crucial to segment the customers intelligently in order to offer more targeted and...
Tianyi Jiang, Alexander Tuzhilin
CVPR
2012
IEEE
11 years 9 months ago
A tiered move-making algorithm for general pairwise MRFs
A large number of problems in computer vision can be modeled as energy minimization problems in a markov random field (MRF) framework. Many methods have been developed over the y...
Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr
ICDAR
2007
IEEE
14 years 1 months ago
Handwritten Word Recognition Using Conditional Random Fields
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
CVIU
2008
180views more  CVIU 2008»
13 years 7 months ago
Topology cuts: A novel min-cut/max-flow algorithm for topology preserving segmentation in N-D images
Topology is an important prior in many image segmentation tasks. In this paper, we design and implement a novel graph-based min-cut/max-flow algorithm that incorporates topology p...
Yun Zeng, Dimitris Samaras, Wei Chen, Qunsheng Pen...