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Real-time pattern recognition. II. Visual conjunctoid neural networks

机译:实时模式识别。二。视觉结膜神经网络

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For pt.I, see ibid., p.580-3 (1991). Keping Ma (1991) studied alternative approached to airplane recognition. In one comparative study, he evaluated various forms of conjunctoid and normal model performance, based on conjunctive features such as the number of acute, right, and obtuse angles appearing in the visual contour of an airplane. In this paper, the authors first review some Ma's related results. They then describe some of the mathematical details associated with the conjunctoid counterpart to the normal model. The authors also describe some preliminary steps toward automating the feature selection process for conjunctoid neural networks in airplane recognition settings, with an eye toward developing a quite general automatic data processing framework.
机译:关于第一点,请参见同上,第580-3页(1991)。马可平(1991)研究了飞机识别的替代方法。在一项比较研究中,他根据诸如飞机视觉轮廓中出现的锐角,直角和钝角的数量之类的联合特征,评估了各种形式的结膜和正常模型的性能。在本文中,作者首先回顾了马云的一些相关结果。然后,他们描述了与正常模型的结膜对应物相关的一些数学细节。作者还描述了在飞机识别环境中使结膜神经网络的特征选择过程自动化的一些初步步骤,着眼于开发相当通用的自动数据处理框架。

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