- author = "Neal R. Harvey and James Theiler and Steven P. Brumby and Simon Perkins and John J. Szymanski and Jeffrey J. Bloch and Reid B. Porter and Mark Galassi and A. Cody Young",
- title = "Comparison of {GENIE} and conventional supervised classifiers for multispectral image feature extraction",
- journal = "IEEE Transactions on Geoscience and Remote Sensing",
- year = "2002",
- volume = "40",
- number = "2",
- pages = "393--404",
- month = feb,
- keywords = "genetic algorithms, genetic programming, Supervised Classification, Image Processing, Evolutionary Algorithms, Multispectral Imagery, Remote Sensing, feature extraction, geophysical signal processing, geophysical techniques, geophysics computing, image classification, multidimensional signal processing, terrain mapping, GENIE, GENetic Imagery Exploitation, IR, feature extraction, geophysical measurement technique, hybrid evolutionary algorithm, image classification, image processing, infrared, land surface, multispectral remote sensing, supervised classifier, terrain mapping, visible",
- ISSN = "0196-2892",
-
URL = "
http://nis-www.lanl.gov/~simes/webdocs/harveyIEEE_TGARS2001.pdf",
-
URL = "
http://citeseer.ist.psu.edu/561309.html",
-
DOI = "
doi:10.1109/36.992801",
- size = "12 pages",
- abstract = "We have developed an automated feature detection/ classification system, called Genie (GENetic Imagery Exploitation), which has been designed to generate image processing pipelines for a variety of feature detection/ classification tasks. Genie is a hybrid evolutionary algorithm that addresses the general problem of finding features of interest in multi-spectral remotely-sensed images. We describe our system in detail together with experiments involving comparisons of Genie with several conventional supervised classification techniques, for a number of classification tasks using multi-spectral remotely-sensed imagery.",
-
notes = "On line version not identical to IEEE version
Inspec Accession Number: 7265352, CODEN: IGRSD2",
