2006
NIPS
NeurIPS 2006
A selective attention multi--chip system with dynamic synapses and spiking neurons
Abstract
Selective attention is the strategy used by biological sensory systems to solve the problem of limited parallel processing capacity: salient subregions of the input stimuli are serially processed, while nonsalient regions are suppressed. We present an mixed mode analog/digital Very Large Scale Integration implementation of a building block for a multichip neuromorphic hardware model of selective attention. We describe the chip's architecture and its behavior, when its is part of a multichip system with a spiking retina as input, and show how it can be used to implement in real-time flexible models of bottom-up attention.
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Conference Pioneer
— NIPS 2006
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Vision and Deep Learning
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Trend Setter
— Multimodal Learning
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Keyword Pioneer
— neuromorphic hardware
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Reinforcement Learning
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Hot Topic Early Bird
— real-time processing
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Deep Learning > Architectures > Neural Networks
Computer Vision > Analysis > Scene Understanding
Computer Science > Systems > Distributed Systems
Interdisciplinary > Cognitive Science > Perception
Artificial Intelligence > Core AI > Computer Vision