Comparison between Frame-Constrained Fix-Pixel-Value and Frame-Free Spiking-Dynamic-Pixel ConvNets for Visual Processing.
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Real-time classification and sensor fusion with a spiking deep belief network.Spatiotemporal features for asynchronous event-based data.The ripple pond: enabling spiking networks to see.Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.Feature Representations for Neuromorphic Audio Spike Streams.A Configurable Event-Driven Convolutional Node with Rate Saturation Mechanism for Modular ConvNet Systems Implementation.Deep Learning With Spiking Neurons: Opportunities and Challenges
P2860
Q21129359-254FF89C-EBBE-4849-8EEB-5EF37710C0FBQ30908451-8858B3BA-38E8-46C7-8D98-F543B75C53E3Q42905366-5845B48D-2685-4986-B0ED-B44E11914870Q49632686-42CF788A-21D3-4017-8CC8-CFDB6594EC2CQ50274155-FACBB190-A782-4B0E-A16D-23F8216B34A5Q53439393-60287598-0B26-4E88-B187-2752A6704643Q58556508-EABD23DB-69C9-4E60-AF2F-14C31BCA50EF
P2860
Comparison between Frame-Constrained Fix-Pixel-Value and Frame-Free Spiking-Dynamic-Pixel ConvNets for Visual Processing.
description
2012 nî lūn-bûn
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2012年の論文
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2012年論文
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2012年論文
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2012年論文
@zh-hk
2012年論文
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2012年論文
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2012年论文
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2012年论文
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2012年论文
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name
Comparison between Frame-Const ...... onvNets for Visual Processing.
@en
type
label
Comparison between Frame-Const ...... onvNets for Visual Processing.
@en
prefLabel
Comparison between Frame-Const ...... onvNets for Visual Processing.
@en
P2093
P2860
P356
P1476
Comparison between Frame-Const ...... ConvNets for Visual Processing
@en
P2093
Alejandro Linares-Barranco
Bernabe Linares-Barranco
Carlos Zamarreño-Ramos
Clément Farabet
Eugenio Culurciello
Rafael Paz
Yann Lecun
P2860
P356
10.3389/FNINS.2012.00032
P577
2012-04-10T00:00:00Z