Onboard Evolutionary Risk Recognition System for Automobiles Toward the Risk Map System
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Ogawa:2007:TIE,
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author = "Genya Ogawa and Katsuyuki Kise and Tsuyoshi Torii and
Tomoharu Nagao",
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title = "Onboard Evolutionary Risk Recognition System for
Automobiles Toward the Risk Map System",
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journal = "IEEE Transactions on Industrial Electronics",
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year = "2007",
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volume = "54",
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number = "2",
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pages = "878--886",
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month = apr,
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keywords = "genetic algorithms, genetic programming, automobiles,
image recognition, risk analysis automobiles, human
recognition, image recognition processing, on board
camera system, pedestrian detection, risk map system,
risk recognition system, vehicle driving",
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DOI = "doi:10.1109/TIE.2007.891654",
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ISSN = "0278-0046",
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size = "9 pages",
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abstract = "To achieve a system that improves the safety and
comfort of the vehicle driving, a recognition system
equivalent to the human recognition ability should be
developed. However, the vehicle environment is
complicated and involves situations so diverse that a
uniform recognition processing approach cannot function
sufficiently. For a solution to this problem, we have
been studying a comprehensive risk recognition system,
which we call the risk map system, with learning
capability. As part of this paper, a system has been
developed that autonomously obtains the image
recognition processing. This paper presents a system as
an example that automatically learns through genetic
programming to obtain the image processing of
pedestrians and vehicles taken by an onboard camera
system",
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notes = "picking out pedestrian silhouettes from 256 gray level
CCD image sequences (4 frames). ACTIT. bloat size
penalty. 500 generations. Fuji Heavy Industries Ltd.",
- }
Genetic Programming entries for
Genya Ogawa
Katsuyuki Kise
Tsuyoshi Torii
Tomoharu Nagao
Citations