- author = "Gayan Wijesinghe and Vic Ciesielski",
- title = "Using Restricted Loops in Genetic Programming for Image Classification",
- booktitle = "2007 IEEE Congress on Evolutionary Computation",
- year = "2007",
- editor = "Dipti Srinivasan and Lipo Wang",
- pages = "4569--4576",
- address = "Singapore",
- month = "25-28 " # sep,
- organization = "IEEE Computational Intelligence Society",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, STGP, greyscale image classification, infinite loops, invalid programs, no-loop method accuracy, restricted loops, image classification",
- ISBN = "1-4244-1340-0",
- file = "1664.pdf",
-
DOI = "
doi:10.1109/CEC.2007.4425070",
-
abstract = "Loops are rarely used in genetic programming due to
issues such as detecting infinite loops and invalid
programs. In this paper we present a restricted form of
loops that is specifically designed to be evolved in
image classifiers. Particularly, we evolve classifiers
that use these loops to perform calculations on image
regions chosen by the loops. We have compared this
method to another classification method that only uses
individual pixels in its calculations.
These two methods are tested on two synthesised and one non-synthesised grey scale image classification problems of varying difficulty. The most difficult problem requires determining heads or tails of 320 by 320 pixel images of a US one cent coin at any angle. On this problem, the accuracy of the loops approach was 97.80% in contrast to the no-loop method accuracy of 79.46%. Use of loops also reduces over fitting of training data. We also found that loop methods overfit less when only a few training examples are available.",
-
notes = "CEC 2007 - A joint meeting of the IEEE, the EPS, and
the IET.
IEEE Catalog Number: 07TH8963C",
