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GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
15 years 4 months ago
Objective reduction using a feature selection technique
This paper introduces two new algorithms to reduce the number of objectives in a multiobjective problem by identifying the most conflicting objectives. The proposed algorithms ar...
Antonio López Jaimes, Carlos A. Coello Coel...
ICCV
2007
IEEE
16 years 5 months ago
Multi-Object Tracking Through Clutter Using Graph Cuts
The standard graph cut technique is a robust method for globally optimal image segmentations. However, because of its global nature, it is prone to capture outlying areas similar ...
Allen Tannenbaum, James G. Malcolm, Yogesh Rathi
ICCV
2003
IEEE
16 years 5 months ago
A New Paradigm for Recognizing 3-D Object Shapes from Range Data
Most of the work on 3-D object recognition from range data has used an alignment-verification approach in which a specific 3-D object is matched to an exact instance of the same o...
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Mei...
ICCV
1999
IEEE
16 years 5 months ago
Object Recognition from Local Scale-Invariant Features
Proc. of the International Conference on Computer Vision, Corfu (Sept. 1999) An object recognition system has been developed that uses a new class of local image features. The fea...
David G. Lowe
ADMA
2009
Springer
145views Data Mining» more  ADMA 2009»
15 years 10 months ago
A Framework for Multi-Objective Clustering and Its Application to Co-Location Mining
The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, arch...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricar...