ID | 19718 |
Eprint ID | 19718
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FullText URL | |
Author |
Ando Jun
Nagao Tomoharu
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Abstract | 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.
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Published Date | 2009-11-12
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Publication Title |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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Volume | volume2009
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Issue | issue1
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Publisher | IEEE SMC Hiroshima Chapter
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Start Page | 296
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End Page | 301
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ISSN | 1883-3977
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NCID | BB00577064
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Content Type |
Conference Paper
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language |
English
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Copyright Holders | IEEE SMC Hiroshima Chapter
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Event Title | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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Event Location | 東広島市
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Event Location Alternative | Higashi-Hiroshima City
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File Version | publisher
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Refereed |
True
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Eprints Journal Name | IWCIA
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