Live Demonstration: Real-time Event-driven Object Recognition on SpiNNaker

被引：0
|
作者：
Orchard, Garrick [1 ]
Lagorce, Xavier [2 ,3 ,4 ]
Posch, Christoph [2 ,3 ,4 ]
Furber, Steve [5 ]
Benosman, Ryad [2 ,3 ,4 ]
Galluppi, Francesco [2 ,3 ,4 ]
机构：
[1] Natl Univ Singapore, Singapore Inst Neurotechnol SINAPSE, Singapore 117548, Singapore
[2] Univ Paris 06, Sorbonne Univ, UMR S 968, Inst Vis, Paris, France
[3] INSERM, U968, Paris, France
[4] CNRS, UMR 7210, Paris, France
[5] Univ Manchester, Adv Processor Technol Grp, Manchester M13 9PL, Lancs, England
来源：
2015 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2015年
基金：
英国工程与自然科学研究理事会;
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This live demonstration shows real-time visual object recognition based on a spiking neural network adaptation of the HMAX model running on a purely event-based computational hardware platform. Visual input to the system is provided by an ATIS spiking silicon retina sensor. A SpiNNaker board processes the event-encoded visual information from the scene. Using a Leaky Integrate-and-Fire (LIF) neuron model implemented on SpiNNaker, an event-driven, multi-layer network is created that performs real-time orientation extraction and recombination. In this demonstration, the network will be tuned to recognize complex objects such as printed characters.
引用
收藏
页码：1903 / 1903
页数：1
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