Live demonstration: Real-time event-driven object recognition on SpiNNaker

Garrick Orchard; Xavier Lagorce; Christoph Posch; Stephen Furber; Ryad Benosman; Francesco Galluppi

doi:10.1109/ISCAS.2015.7169036

Live demonstration: Real-time event-driven object recognition on SpiNNaker

Garrick Orchard, Xavier Lagorce, Christoph Posch, Stephen Furber, Ryad Benosman, Francesco Galluppi

Advanced Processor Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Proceedings - IEEE International Symposium on Circuits and Systems
Publisher	IEEE
Pages	1903
Number of pages	1
Volume	2015-July
ISBN (Print)	9781479983919
DOIs	https://doi.org/10.1109/ISCAS.2015.7169036
Publication status	Published - 27 Jul 2015
Event	IEEE International Symposium on Circuits and Systems, ISCAS 2015 - Lisbon, Portugal Duration: 24 May 2015 → 27 May 2015 http://www.scopus.com/inward/record.url?eid=2-s2.0-84946225388&partnerID=40&md5=58467212fe9944b83fe45c3ea4058d6b

Conference

Conference	IEEE International Symposium on Circuits and Systems, ISCAS 2015
Country/Territory	Portugal
City	Lisbon
Period	24/05/15 → 27/05/15
Internet address	http://www.scopus.com/inward/record.url?eid=2-s2.0-84946225388&partnerID=40&md5=58467212fe9944b83fe45c3ea4058d6b

Access to Document

10.1109/ISCAS.2015.7169036

Cite this

@inproceedings{cbe4d10f947249e0a3e202850792ab24,

title = "Live demonstration: Real-time event-driven object recognition on SpiNNaker",

abstract = "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.",

author = "Garrick Orchard and Xavier Lagorce and Christoph Posch and Stephen Furber and Ryad Benosman and Francesco Galluppi",

year = "2015",

month = jul,

day = "27",

doi = "10.1109/ISCAS.2015.7169036",

language = "English",

isbn = "9781479983919",

volume = "2015-July",

pages = "1903",

booktitle = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "IEEE",

address = "United States",

note = "IEEE International Symposium on Circuits and Systems, ISCAS 2015 ; Conference date: 24-05-2015 Through 27-05-2015",

url = "http://www.scopus.com/inward/record.url?eid=2-s2.0-84946225388&partnerID=40&md5=58467212fe9944b83fe45c3ea4058d6b",

}

Orchard, G, Lagorce, X, Posch, C, Furber, S, Benosman, R & Galluppi, F 2015, Live demonstration: Real-time event-driven object recognition on SpiNNaker. in Proceedings - IEEE International Symposium on Circuits and Systems. vol. 2015-July, 7169036, IEEE, pp. 1903, IEEE International Symposium on Circuits and Systems, ISCAS 2015, Lisbon, Portugal, 24/05/15. https://doi.org/10.1109/ISCAS.2015.7169036

TY - GEN

T1 - Live demonstration

T2 - IEEE International Symposium on Circuits and Systems, ISCAS 2015

AU - Orchard, Garrick

AU - Lagorce, Xavier

AU - Posch, Christoph

AU - Furber, Stephen

AU - Benosman, Ryad

AU - Galluppi, Francesco

PY - 2015/7/27

Y1 - 2015/7/27

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84946198286&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2015.7169036

DO - 10.1109/ISCAS.2015.7169036

M3 - Conference contribution

AN - SCOPUS:84946198286

SN - 9781479983919

VL - 2015-July

SP - 1903

BT - Proceedings - IEEE International Symposium on Circuits and Systems

PB - IEEE

Y2 - 24 May 2015 through 27 May 2015

ER -

Live demonstration: Real-time event-driven object recognition on SpiNNaker

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this