Genetic programming approach to extracting features from remotely sensed imagery
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Brumby:2001:FUSION,
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author = "Steven P. Brumby and James Theiler and
Simon Perkins and Neal R. Harvey and John J. Szymanski",
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title = "Genetic programming approach to extracting features
from remotely sensed imagery",
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booktitle = "FUSION 2001: Fourth International Conference on Image
Fusion",
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year = "2001",
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address = "Montreal, Quebec, Canada",
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month = "7-10 " # aug,
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email = "brumby@lanl.gov",
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keywords = "genetic algorithms, genetic programming, Evolutionary
Computation, Image Processing, Remote Sensing,
Multispectral Imagery, Panchromatic imagery",
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URL = "http://public.lanl.gov/perkins/webdocs/brumbyFUSION2001.pdf",
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size = "8 pages",
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abstract = "Multi-instrument data sets present an interesting
challenge to feature extraction algorithm developers.
Beyond the immediate problems of spatial
co-registration, the remote sensing scientist must
explore a complex algorithm space in which both spatial
and spectral signatures may be required to identify a
feature of interest. We describe a genetic
programming/supervised classifier software system,
called Genie, which evolves and combines
spatio-spectral image processing tools for remotely
sensed imagery. We describe our representation of
candidate image processing pipelines, and discuss our
set of primitive image operators. Our primary
application has been in the field of geospatial feature
extraction, including wildfire scars and general
land-cover classes, using publicly available
multi-spectral imagery (MSI) and hyper-spectral imagery
(HSI). Here, we demonstrate our system on Landsat 7
Enhanced Thematic Mapper (ETM+) MSI. We exhibit an
evolved pipeline, and discuss its operation and
performance.",
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notes = "oai:CiteSeerPSU:567526 seems to be wrong",
- }
Genetic Programming entries for
Steven P Brumby
James Theiler
Simon Perkins
Neal R Harvey
John J Szymanski
Citations