Pragmatic Genetic Programming strategy for the problem of vehicle detection in airborne reconnaissance

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

@Article{howard:2006:PRL,

• author = "Daniel Howard and Simon C. Roberts and Conor Ryan",
• title = "Pragmatic Genetic Programming strategy for the problem of vehicle detection in airborne reconnaissance",
• journal = "Pattern Recognition Letters",
• year = "2006",
• volume = "27",
• number = "11",
• pages = "1275--1288",
• month = aug,
• note = "Evolutionary Computer Vision and Image Understanding",
• keywords = "genetic algorithms, genetic programming, Object detection, Method of stages, Reconnaissance, Discrete Fourier transform, Vehicle detection, Machine vision",
• DOI = "doi:10.1016/j.patrec.2005.07.025",
• abstract = "A Genetic Programming (GP) method uses multiple runs, data decomposition stages, to evolve a hierarchical set of vehicle detectors for the automated inspection of infrared line scan imagery that has been obtained by a low flying aircraft. The performance on the scheme using two different sets of GP terminals (all are rotationally invariant statistics of pixel data) is compared on 10 images. The discrete Fourier transform set is found to be marginally superior to the simpler statistics set that includes an edge detector. An analysis of detector formulae provides insight on vehicle detection principles. In addition, a promising family of algorithms that take advantage of the GP method's ability to prescribe an advantageous solution architecture is developed as a post-processor. These algorithms selectively reduce false alarms by exploring context, and determine the amount of contextual information that is required for this task.",

}

Genetic Programming entries for Daniel Howard Simon C Roberts Conor Ryan

Citations