首页> 外文期刊>International Journal of Intelligent Systems Technologies and Applications >Recognition of benzene structure from handwritten chemical expression with radial basis function neural network and rule-based approach
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Recognition of benzene structure from handwritten chemical expression with radial basis function neural network and rule-based approach

机译:用径向基础函数神经网络和规则的方法识别手写化学表达与基于规则的方法

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>The chemical symbols and structures are basic building blocks of chemical expressions and reactions. Benzene symbol is widely used in aromatic chemical reactions. In this paper, we attempt to build a system which can recognise a benzene symbol from the handwritten chemical expressions, reactions or statements (HCERS). In this work a classifier has been developed. It identifies the parts of an image, which can possibly represent a benzene symbol from HCERS. On the next stage, i.e., recognition, the correct benzene structure is recognised from the identified parts of images. Two approaches, first rule based and second radial basis function neural network (RBFNN) based, have been proposed for the classifier. The scanned image of the handwritten chemical reaction, expressions or statements is input to our system. The output shows the presence of valid benzene ring structure or otherwise in the scanned image.
机译:>化学符号和结构是化学表达和反应的基本构建块。 苯符号广泛用于芳香化学反应。 在本文中,我们试图建立一个系统,该系统可以识别手写化学表达,反应或陈述(HCERS)的苯符号。 在这项工作中,已经开发了分类器。 它识别图像的部分,这可能代表来自HCERS的苯符号。 在下一阶段,即识别,从鉴定的图像部分识别正确的苯结构。 已经提出了两种方法,基于基于规则和第二径向基函数神经网络(RBFNN)的分类器。 手写化学反应,表达或陈述的扫描图像是输入我们的系统。 输出显示存在有效的苯环结构或以其他方式在扫描图像中。

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