Object Detection using Neural Networks and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Barret Chin and Mengjie Zhang",
  title =        "Object Detection using Neural Networks and Genetic
  institution =  "Computer Science, Victoria University of Wellington",
  year =         "2007",
  type =         "Technical report",
  number =       "CS-TR-07-3",
  address =      "New Zealand",
  month =        nov,
  keywords =     "genetic algorithms, genetic programming, object
                 detection, neural networks, region refinement, feature
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-07/CS-TR-07-3.pdf",
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-07-3.abs.html",
  abstract =     "This paper describes a domain independent approach to
                 the use of neural networks (NNs) and genetic
                 programming (GP) for object detection problems. Instead
                 of using high level features for a particular task,
                 this approach uses domain independent pixel statistics
                 for object detection. The paper first compares an NN
                 method and a GP method on four image data sets
                 providing object detection problems of increasing
                 difficulty. The results show that the GP method
                 performs better than the NN method on these problems
                 but still produces a large number of false alarms on
                 the difficult problem and computation cost is still
                 high. To deal with these problems, we develop a new
                 method called GP-refine that uses a two stage learning
                 process. The results suggest that the new GP method
                 further improves object detection performance on the
                 difficult object detection task.",
  size =         "pages 13",

Genetic Programming entries for Barret Chin Mengjie Zhang