集成数字CNN摄像机的设计空间探索

S. Malki, L. Spaanenburg
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引用次数: 0

摘要

CNN技术的主要推动力是模拟实现。数字实现的早期尝试具有有限的潜力,例如限制了对B/W图像的线性算法的使用。本文展望了成功整合CNN全部潜力的前景。这需要仔细调整内存和片上网络带宽,以适应神经节点的时间/空间方面。本文介绍了一种探索模型,并讨论了架构及其在流灰度图像中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design space exploration for the integrated digital CNN camera
The main thrust of CNN technology has been in analog implementations. Early attempts for digital implementations have a limited potential, confining the usage to for instance linear algorithms for B/W pictures. The paper looks into the prospects of successfully integrating the full CNN potential. This requires a carefully tuning of memory and network-on-chip bandwidth to the temporal/spatial aspects of the neural nodes. The paper introduces an exploration model and discusses architecture with application to streaming grey-scale images.
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