一个用于对象识别的神经专家架构

International 1989 Joint Conference on Neural Networks Pub Date : 1989-12-01 DOI:10.1109/IJCNN.1989.118315

J. Selinsky, A. Guez, J. Eilbert, M. Kam

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引用次数: 0

摘要

仅给出摘要形式，如下。本文报道了基于神经网络/专家系统(neural -expert)结构的物体识别实验结果。概述了实验对象识别系统的神经专家体系结构。结果报告了一个20模式的原型集的合成二值图像的识别放置在任意旋转。在无噪声条件下，识别率达到100%。加入1%和2%随机像素噪声后，识别率分别达到95.2%和89.5%

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A neuro-expert architecture for object recognition

Summary form only given, as follows. A report is presented on results of experiments in object recognition with a combined neural network/expert system architecture (neuro-expert). The neuro-expert architecture is outlined with a description of the experimental object recognition system. Results are reported for the recognition of a 20-pattern prototype set of synthesized binary images placed at arbitrary rotations. A 100% recognition rate was obtained under noiseless conditions. Addition of 1% and 2% random pixel noise resulted in recognition rates of 95.2% and 89.5%, respectively.<>

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International 1989 Joint Conference on Neural Networks

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