Evaluation of oak wilt index based on genetic programming

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@InProceedings{Uto:2009:WHISPERS,

• author = "Kuniaki Uto and Yukio Kosugi and Toshinari Ogatay",
• title = "Evaluation of oak wilt index based on genetic programming",
• booktitle = "First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS '09",
• year = "2009",
• month = aug,
• pages = "1--4",
• keywords = "genetic algorithms, genetic programming, binary operations, extraction performance, normalized oak wilt index, physically interpretable index, plant physiology, remotely sensed hyperspectral image, tree construction, image processing, vegetation mapping",
• DOI = "doi:10.1109/WHISPERS.2009.5289107",
• abstract = "We proposed a normalized oak wilt index (NWI) to extract oak wilt area from remotely sensed hyperspectral image of forest in our previous work. The NWI, which is designed based on factitious characterization of spectral profiles of oak wilt, realised satisfactory extraction performance. In this paper, we propose a genetic-programming-based search method for physically interpretable index. The search procedure consists of two stages, i.e. extraction for significant binary operations and tree construction, in expectation of dealing with more subtle problem, e.g. estimation of quantities of ingredients of vegetation. The selected binary operations are consistent with plant physiology. The extraction performance of proposed method based on fewer binary operations stands comparison with NWI's performance.",
• notes = "Also known as \cite{5289107}",

}

Genetic Programming entries for Kuniaki Uto Yukio Kosugi Toshinari Ogatay

Citations