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IFSR 2005 >
このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/3950
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| タイトル: | Malaysian License Plate Recognition Using Artificial Neural Networks and Evolutionally Computation |
| 著者: | Stephen, Karungaru
Fukumi, Minoru
Akamatsu, Norio |
| キーワード: | license plate recognition
neural networks
genetic algorithms |
| 発行日: | Nov-2005 |
| 出版者: | JAIST Press |
| 抄録: | In this paper, a license plate recognition method using neural networks and genetic algorithms is proposed. Our system assumes that license plate localization has already been accomplished. We combine two methods into a hybrid system to recognize the license plate’s characters. In the first method, we train neural networks to recognize the characters and then apply a genetic algorithm to guide the neural network in the search. The genetic algorithm is necessary because of size and orientation differences between the neural network training samples and the test characters. The other method is template matching that also uses the genetic algorithm to guide its search for same reasons as in the first method. This work is performed with speed and accuracy in mind, aiming at the online usage of the system. The final system accuracy achieved is 97.3 %. |
| 記述: | The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2160, Kobe, Japan
Symposium 3, Session 7 : Intelligent Information Technology and Applications Computational Intelligence (1) |
| 言語: | ENG |
| URI: | http://hdl.handle.net/10119/3950 |
| ISBN: | 4-903092-02-X |
| 出現コレクション: | IFSR 2005
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このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
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| 20151.pdf | | 52Kb | Adobe PDF | 見る/開く |
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