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Event-Based Attention and Tracking on Neuromorphic Hardware


Renner, Alpha; Evanusa, Matthew; Orchard, Garrick; Sandamirskaya, Yulia (2020). Event-Based Attention and Tracking on Neuromorphic Hardware. In: 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Genova, Italy, 31 August 2020 - 2 September 2020.

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.

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.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:2 September 2020
Deposited On:03 Feb 2021 11:15
Last Modified:16 Feb 2021 04:41
Publisher:IEEE
ISBN:9781728149226
OA Status:Green
Publisher DOI:https://doi.org/10.1109/aicas48895.2020.9073789

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