三维物体的定向耦合神经网络识别

Y. Miyanaga, K. Motoyoshi, K. Tochinai
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引用次数: 1

摘要

本文介绍了一种三维物体识别系统的新方法。该系统基于一种受限的多层神经网络。为了大大减少识别预处理的总计算量,在网络中引入了方向耦合节点。实验结果表明,该系统能够正确识别部分三维物体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of three dimensional objects using a directional coupled neural network
This report introduces a new approach on a recognition system of three dimensional, i.e., 3-D, objects. The proposed system is based on a restricted multi-layered neural network. In order to greatly reduce the total calculation cost of preprocessing for the recognition, directional coupled nodes in a network are introduced. This report also shows that the system can recognize some 3-D objects correctly in experiments.
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