Naylor D, Jones S, Myers D, Vincent J
Department of Electronic and Electrical Engineering, Loughborough University of Technology, Leicestershire, England.
Int J Neural Syst. 1993 Dec;4(4):337-49. doi: 10.1142/s0129065793000286.
The application of artificial neural networks to real-time image processing tasks requires the use of dedicated, high performance hardware. A linear array processor called HANNIBAL has been developed which implements the backpropagation neural learning algorithm on-chip. This paper considers the design of a complete neural system which integrates HANNIBAL into an existing image processing environment. The goals for the design of the system have been set partly by the primary application, namely feature recognition, but mainly by the desire for a flexible, high performance hardware tool for the study and evaluation of range of neural image processing applications.
将人工神经网络应用于实时图像处理任务需要使用专用的高性能硬件。一种名为汉尼拔（HANNIBAL）的线性阵列处理器已经开发出来，它能在芯片上实现反向传播神经学习算法。本文考虑了一个完整神经系统的设计，该系统将汉尼拔（HANNIBAL）集成到现有的图像处理环境中。该系统设计的目标部分由主要应用（即特征识别）设定，但主要是出于对一种灵活、高性能硬件工具的需求，用于研究和评估一系列神经图像处理应用。
