Multi-Objective Genetic Programming for object detection

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Liddle:2010:cec,

• author = "Thomas Liddle and Mark Johnston and Mengjie Zhang",
• title = "Multi-Objective Genetic Programming for object detection",
• booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4244-6910-9",
• abstract = "In object detection, the goals of successfully discriminating between different kinds of objects (object classification) and accurately identifying the positions of all objects of interest in a large image (object localisation) are potentially in conflict. We propose a Multi-Objective Genetic Programming (MOGP) approach to the task of providing a decision-maker with a diverse set of alternative object detection programs that balance between high detection rate and low false-alarm rate. Experiments on two datasets, simple shapes and photographs of coins, show that it is difficult for a Single-Objective GP (SOGP) system (which weights the multiple objectives a priori) to evolve effective object detectors, but that an MOGP system is able to evolve a range of effective object detectors more efficiently.",
• DOI = "doi:10.1109/CEC.2010.5586072",
• notes = "WCCI 2010. Also known as \cite{5586072}",

}

Genetic Programming entries for Thomas Liddle Mark Johnston Mengjie Zhang

Citations