Onboard Evolutionary Risk Recognition System for Automobiles Toward the Risk Map System

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Ogawa:2007:TIE,

• author = "Genya Ogawa and Katsuyuki Kise and Tsuyoshi Torii and Tomoharu Nagao",
• title = "Onboard Evolutionary Risk Recognition System for Automobiles Toward the Risk Map System",
• journal = "IEEE Transactions on Industrial Electronics",
• year = "2007",
• volume = "54",
• number = "2",
• pages = "878--886",
• month = apr,
• 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",
• DOI = "doi:10.1109/TIE.2007.891654",
• ISSN = "0278-0046",
• size = "9 pages",
• 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",
• 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