Application issues of a programmable optical CNN implementation

L. Orzó, S.T. Kes, T. Roska
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引用次数: 2

Abstract

A programmable opto-electronic analogic CNN computer (POAC) provides an efficient frame for diverse image processing applications, as it combines the enormous inherent computational capabilities of our new, massively parallel, but flexibly programmable optical CNN implementation with the capabilities of a visual CNN-UM chip. Our optical CNN implementation is based on an original, semi-incoherent optical correlator architecture, which is superior to other optical implementations in several respects. It makes real time reprogramming of a new type of joint Fourier transform correlator (t/sub 2/-JTC) possible while preserving the inherent speed of VanderLugt type of systems. Furthermore the POAC architecture overcomes the main limitations of both the microelectronic (VLSI) and other optical implementations. In this paper it will be shown that this device is particularly useful in image-processing algorithms, which cannot be fulfilled real time by any other existing optical or digital system due to the high number of pattern matching tasks required.
可编程光学CNN实现的应用问题
可编程光电模拟CNN计算机(POAC)为各种图像处理应用提供了一个有效的框架,因为它结合了我们新的、大规模并行的、灵活的可编程光学CNN实现的巨大固有计算能力和视觉CNN- um芯片的能力。我们的光学CNN实现基于原始的半非相干光学相关器架构,在几个方面优于其他光学实现。它使一种新型联合傅里叶变换相关器(t/sub 2/-JTC)的实时重编程成为可能,同时保持VanderLugt型系统的固有速度。此外,POAC架构克服了微电子(VLSI)和其他光学实现的主要限制。在本文中,它将表明,该设备是特别有用的图像处理算法,不能实现实时的任何其他现有的光学或数字系统,由于需要大量的模式匹配任务。
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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