MFNN图像配准的FPGA实现

2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings. Pub Date : 2002-12-16 DOI:10.1109/FPT.2002.1188712

D. Gharpure, M. Puranik

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引用次数: 2

摘要

对多层前馈神经网络(MFNN)进行了改进，简化了硬件实现，同时保持了检测的准确性。所得结果与软件仿真算法相当，并作为测试基础。MFNN的实现具有硬件复杂度低、抗噪性好、电路速度快等特点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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FPGA implementation of MFNN for image registration

The multilayer feedforward neural network (MFNN) is modified to simplify hardware realization and at the same time retain the accuracy of detection. The results obtained have been found to be comparable to the software simulation algorithm which is used as a test base. The MFNN implementation involves low hardware complexity, good noise immunity and fast circuitry.

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2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings.

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