Using Loops in Genetic Programming for a Two Class Binary Image Classification Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{LiCie04,

• author = "Xiang Li and Vic Ciesielski",
• title = "Using Loops in Genetic Programming for a Two Class Binary Image Classification Problem",
• booktitle = "AI 2004: Advances in Artificial Intelligence: Proceedings of the 17th Australian Joint Conference on Artificial Intelligence",
• year = "2004",
• editor = "Geoffrey I. Webb and Xinghuo Yu",
• volume = "3339",
• series = "Lecture Notes in Computer Science",
• pages = "898--909",
• address = "Cairns, Australia",
• month = dec # " 4-6",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, image classification, classification problem",
• ISBN = "3-540-24059-4",
• DOI = "doi:10.1007/b104336",
• abstract = "Loops are rarely used in genetic programming (GP), because they lead to massive computation due to the increase in the size of the search space. We have investigated the use of loops with restricted semantics for a problem in which there are natural repetitive elements, that of distinguishing two classes of images. Using our formulation, programs with loops were successfully evolved and performed much better than programs without loops. Our results suggest that loops can successfully used in genetic programming in situations where domain knowledge is available to provide some restrictions on loop semantics.",

}

Genetic Programming entries for Xiang Li Victor Ciesielski

Citations