Evolution of Vehicle Detectors for Infrared Linescan Imagery
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{roberts:1999:evdIRLI,
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author = "Simon C. Roberts and Daniel Howard",
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title = "Evolution of Vehicle Detectors for Infrared Linescan
Imagery",
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booktitle = "Evolutionary Image Analysis, Signal Processing and
Telecommunications: First European Workshop, EvoIASP'99
and EuroEcTel'99",
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year = "1999",
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editor = "Riccardo Poli and Hans-Michael Voigt and
Stefano Cagnoni and Dave Corne and George D. Smith and
Terence C. Fogarty",
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volume = "1596",
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series = "LNCS",
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pages = "110--125",
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address = "Goteborg, Sweden",
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publisher_address = "Berlin",
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month = "28-29 " # may,
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organisation = "EvoNet",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-65837-8",
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DOI = "doi:10.1007/10704703_9",
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abstract = "The paper addresses an important and difficult problem
of object recognition in poorly constrained
environments and with objects having large variability.
This research uses genetic programming (GP) to develop
automatic object detectors. The task is to detect
vehicles in infrared line scan (IRLS) images gathered
by low flying aircraft. This is a difficult task due to
the diversity of vehicles and the environments in which
they can occur, and because images vary with numerous
factors including fly-over, temporal and weather
characteristics. A novel multi-stage approach is
presented which addresses automatic feature detection,
automatic object segregation, rotation invariance and
generalisation across diverse objects whilst
discriminating from a myriad of potential non-objects.
The approach does not require imagery to be
pre-processed.",
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notes = "EvoIASP99'99",
- }
Genetic Programming entries for
Simon C Roberts
Daniel Howard
Citations