Sparse Temporal Encoding of Visual Features for Robust Object Recognition by Spiking Neurons

Robust object recognition in spiking neural systems remains a challenging in neuromorphic computing area as it needs to solve both the effective encoding of sensory information and also its integration with downstream learning neurons. We target this problem by developing a spiking neural system con...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2018-12, Vol.29 (12), p.5823-5833
Hauptverfasser:	Zheng, Yajing, Li, Shixin, Yan, Rui, Tang, Huajin, Tan, Kay Chen
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classifiers Coding Encoding Feature extraction Feature recognition Firing pattern Learning Model accuracy Neurons Object recognition Pattern recognition Representations Robust object recognition Robustness Sensory integration sparse temporal encoding spatiotemporal patterns Spatiotemporal phenomena Spiking spiking neural networks (SNNs) temporal classifier Visualization
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