Výsledky vyhledávání - "Kang, Ziyang"

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SeqXFilter: A Memory-efficient Denoising Filter for Dynamic Vision Sensors

Autor: Guo, Shasha, Wang, Lei, Chen, Xiaofan, Zhang, Limeng, Kang, Ziyang, Xu, Weixia

Neuromorphic event-based dynamic vision sensors (DVS) have much faster sampling rates and a higher dynamic range than frame-based imaging sensors. However, they are sensitive to background activity (BA) events that are unwanted. There are some filter

Externí odkaz: http://arxiv.org/abs/2006.01687

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A Noise Filter for Dynamic Vision Sensors using Self-adjusting Threshold

Autor: Guo, Shasha, Kang, Ziyang, Wang, Lei, Zhang, Limeng, Chen, Xiaofan, Li, Shiming, Xu, Weixia

Neuromorphic event-based dynamic vision sensors (DVS) have much faster sampling rates and a higher dynamic range than frame-based imagers. However, they are sensitive to background activity (BA) events which are unwanted. we propose a new criterion w

Externí odkaz: http://arxiv.org/abs/2004.04079

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SNEAP: A Fast and Efficient Toolchain for Mapping Large-Scale Spiking Neural Network onto NoC-based Neuromorphic Platform

Autor: Li, Shiming, Guo, Shasha, Zhang, Limeng, Kang, Ziyang, Wang, Shiying, Shi, Wei, Wang, Lei, Xu, Weixia

Spiking neural network (SNN), as the third generation of artificial neural networks, has been widely adopted in vision and audio tasks. Nowadays, many neuromorphic platforms support SNN simulation and adopt Network-on-Chips (NoC) architecture for mul

Externí odkaz: http://arxiv.org/abs/2004.01639

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