Hardware accelerated convolutional neural networks for synthetic vision systems
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...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0271-4302 2158-1525 |
DOI: | 10.1109/ISCAS.2010.5537908 |