Event-Based Attention and Tracking on Neuromorphic Hardware

被引：0
|
作者：
Renner, Alpha [1 ,2 ]
Evanusa, Matthew [3 ]
Orchard, Garrick [4 ]
Sandamirskaya, Yulia [1 ,2 ]
机构：
[1] UZH, Inst Neuroinformat, Zurich, Switzerland
[2] Swiss Fed Inst Technol, Zurich, Switzerland
[3] Univ Maryland, College Pk, MD 20742 USA
[4] Intel Labs, San Francisco Bay Area, CA USA
来源：
2020 2ND IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2020) | 2020年
关键词：
D O I：
10.1109/aicas48895.2020.9073789
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：132 / 132
页数：1
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