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ID 28460
本文ファイル
Thumnail A1208.pdf 2.66 MB
著者
Ando, Jun
Nagao, Tomoharu
NDC
技術・工学
抄録(英)
Image processing and recognition technologies are required to solve various problems. We have already proposed the system which automatically constructs image processing with Genetic Programming (GP), Automatic Construction of Tree-structural Image Transformation (ACTIT). However, it is difficult to construct an accurate image processing for all training image sets if they have various characteristics. In this paper, we propose ACTIT-Boost which automatically constructs an accurate image processing by employing Adaptive Boosting (AdaBoost) to ACTIT. It learns training image sets and their areas which are difficultly approximated to target images in particular. We show experimentally that ACTIT-Boost is more effective in comparison with ordinary ACTIT.
掲載誌名
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
開始ページ
296
終了ページ
301
出版年月日
2009-11
出版者
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
言語
英語
NII資源タイプ
会議発表論文
広大資料タイプ
会議発表論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
(c) Copyright by IEEE SMC Hiroshima Chapter.
関連情報URL
部局名
工学研究科