18,817 research outputs found

    Automatic Construction of Accurate Image Processing using AdaBoost

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    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

    An Overview of Classifier Fusion Methods

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    A number of classifier fusion methods have been recently developed opening an alternative approach leading to a potential improvement in the classification performance. As there is little theory of information fusion itself, currently we are faced with different methods designed for different problems and producing different results. This paper gives an overview of classifier fusion methods and attempts to identify new trends that may dominate this area of research in future. A taxonomy of fusion methods trying to bring some order into the existing “pudding of diversities” is also provided

    An Overview of Classifier Fusion Methods

    Get PDF
    A number of classifier fusion methods have been recently developed opening an alternative approach leading to a potential improvement in the classification performance. As there is little theory of information fusion itself, currently we are faced with different methods designed for different problems and producing different results. This paper gives an overview of classifier fusion methods and attempts to identify new trends that may dominate this area of research in future. A taxonomy of fusion methods trying to bring some order into the existing “pudding of diversities” is also provided
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