Decision Fusion and Reliability Control in Handwritten Digit Recognition System
Decision Fusion and Reliability Control in Handwritten Digit Recognition System
复制标题
手写数字识别系统的决策融合与可靠性控制
DOI：
10.2498/cit.2002.04.03
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Dejan Gorgevik
中科院分区：
文献类型：
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作者：
D. Cakmakov;V. Radevski;Younès Bennani;Dejan Gorgevik
在本文中，合作的两个特征家族的手写数字识别使用委员会的神经网络（NN）分类器将被检查。将研究各种合作方案，并提出相应的结果。为了提高系统的可靠性，我们将使用基于规则和统计合作的多级分类来升级委员会方案。基于规则的合作，使各种拒绝标准的一个简单而有效的实施，而统计合作提供了更好的可能性微调的识别与可靠性权衡。最后的系统已经实现了基于规则的推理与拒绝标准的分类决策融合和广义委员会合作计划的分类被拒绝的数字模式。所提出的结果表明，我们提出了一个成功的方法，在委员会分类器的环境中的可靠性控制，并表明一个合适的合作，统计和基于规则的决策融合是一个很有前途的方法，在手写识别系统。
In this paper, the cooperation of two feature families for handwritten digit recognition using a committee of Neural Network (NN) classifiers will be examined. Various cooperation schemes will be investigated and corresponding results will be presented. To improve the system reliability,we will upgrade the committee scheme using multistage classification based on rule-based and statistical cooperation. The rule-based cooperation enables an easy and efficient implementation of various rejection criteria while the statistical cooperation offers better possibility for fine-tuning of the recognition versus the reliability tradeoff. The final system has been implemented using rule-based reasoning with rejection criteria for classifier decision fusion and the generalized committee cooperation scheme for classification of the rejected digit patterns. The presented results show that we propose a successful approach for reliability control in committee classifier environment and indicate that a suitable cooperation of statistical and rule-based decision fusion is a promising approach in handwritten recognition systems.