publication . Conference object . Other literature type . 2010

Hardware accelerated convolutional neural networks for synthetic vision systems

Eugenio Culurciello; Yann LeCun; Clément Farabet; Selçuk Talay; Berin Martini; Polina Akselrod;
Open Access
  • Published: 01 May 2010
  • Publisher: IEEE
Abstract
In this paper we present a scalable hardware architecture to implement large-scale convolutional neural networks and state-of-the-art multi-layered artificial vision systems. This system is fully digital and is a modular vision engine with the goal of performing real-time detection, recognition and segmentation of mega-pixel images. We present a performance comparison between a software, FPGA and ASIC implementation that shows a speed up in custom hardware implementations.
Subjects
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: Synthetic vision system, Computer hardware, business.industry, business, Field-programmable gate array, Artificial neural network, Software, Convolutional neural network, Hardware architecture, Modular design, Image segmentation, Computer science
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