Event-Based Attention and Tracking on Neuromorphic Hardware
dc.contributor.author
Renner, Alpha
dc.contributor.author
Evanusa, Matthew
dc.contributor.author
Orchard, Garrick
dc.contributor.author
Sandamirskaya, Yulia
dc.date.accessioned
2020-09-07T08:52:55Z
dc.date.available
2020-05-30T03:17:39Z
dc.date.available
2020-06-05T12:51:02Z
dc.date.available
2020-09-07T08:52:55Z
dc.date.issued
2020
dc.identifier.isbn
978-1-7281-4922-6
en_US
dc.identifier.isbn
978-1-7281-4923-3
en_US
dc.identifier.other
10.1109/AICAS48895.2020.9073789
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/417494
dc.description.abstract
We present a fully event-driven vision and processing system for selective attention and tracking implemented on Intel's neuromorphic research chip, Loihi, directly interfaced with an event-based Dynamic Vision Sensor, DAVIS. The attention mechanism is realized as a recurrent spiking neural network (SNN) that forms sustained activation-bump attractors. The network dynamics support object tracking when distractors are present and when the object slows down or stops.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Event-Based Attention and Tracking on Neuromorphic Hardware
en_US
dc.type
Conference Paper
dc.date.published
2020-04-23
ethz.book.title
2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
en_US
ethz.pages.start
132
en_US
ethz.pages.end
132
en_US
ethz.event
2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS 2020) (virtual)
en_US
ethz.event.location
Genova, Italy
en_US
ethz.event.date
August 31 - September 2, 2020
en_US
ethz.notes
Conference postponed due to Corona virus (COVID-19). Due to the Corona virus (COVID-19) the conference was conducted virtually.
en_US
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02533 - Institut für Neuroinformatik / Institute of Neuroinformatics::09699 - Indiveri, Giacomo / Indiveri, Giacomo
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02533 - Institut für Neuroinformatik / Institute of Neuroinformatics::09699 - Indiveri, Giacomo / Indiveri, Giacomo
ethz.date.deposited
2020-05-30T03:18:00Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-07T08:53:05Z
ethz.rosetta.lastUpdated
2021-02-15T17:01:43Z
ethz.rosetta.versionExported
true
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Conference Paper [37070]