Finding Golf Courses: The Ultra High Tech Approach. Harvey, N.&nbsp;R., Perkins, S., Brumby, S.&nbsp;P., Theiler, J., Porter, R.&nbsp;B., Young, Cody, A., Varghese, A.&nbsp;K., Szymanski, J.&nbsp;J., & Bloch, J.&nbsp;J. In Cagnoni, S., Poli, R., Li, Y., Smith, G., Corne, D., Oates, M.&nbsp;J., Hart, E., Lanzi, Luca, P., Boers, E.&nbsp;J.<nbsp>W., Paechter, B., & Fogarty, T.&nbsp;C., editors, Real-World Applications of Evolutionary Computing, volume 1803, of LNCS, pages 54--64, Edinburgh, 17 April, 2000. Springer-Verlag.
Finding Golf Courses: The Ultra High Tech Approach [pdf]Paper  abstract   bibtex   
The search for a suitable golf course is a very important issue in the travel plans of any modern manager. Modern management is also infamous for its penchant for high-tech gadgetry. Here we combine these two facets of modern management life. We aim to provide the cutting edge manager with a method of finding golf courses from space! In this paper, we present Genie: a hybrid evolutionary algorithm-based system that tackles the general problem of finding features of interest in multi-spectral remotely-sensed images, including, but not limited to, golf courses. Using this system we are able to successfully locate golf courses in 10-channel satellite images of several desirable US locations.

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