Výsledky vyhledávání - "Jiang Chunming"

Akademický článek

Peritoneal dialysis related eosinophilic peritonitis: a case report and review of the literature

Autor: Zhang Qingyan, Xia Yangyang, Zhang Miao, Jiang Chunming

Publikováno v: BMC Nephrology, Vol 24, Iss 1, Pp 1-5 (2023)

Abstract Background Overt eosinophilic peritonitis (EP) is a relatively uncommon complication of peritoneal dialysis (PD), although not rare. Here we reported a case of EP relieved after changing dialysate. Case presentation A 28-year old male patien

Externí odkaz: https://doaj.org/article/f10e00b3274441a8b916c511dac93c66

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KLIF: An optimized spiking neuron unit for tuning surrogate gradient slope and membrane potential

Autor: Jiang, Chunming, Zhang, Yilei

Spiking neural networks (SNNs) have attracted much attention due to their ability to process temporal information, low power consumption, and higher biological plausibility. However, it is still challenging to develop efficient and high-performing le

Externí odkaz: http://arxiv.org/abs/2302.09238

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A noise based novel strategy for faster SNN training

Autor: Jiang, Chunming, Zhang, Yilei

Spiking neural networks (SNNs) are receiving increasing attention due to their low power consumption and strong bio-plausibility. Optimization of SNNs is a challenging task. Two main methods, artificial neural network (ANN)-to-SNN conversion and spik

Externí odkaz: http://arxiv.org/abs/2211.05453

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Spiking sampling network for image sparse representation and dynamic vision sensor data compression

Autor: Jiang, Chunming, Zhang, Yilei

Sparse representation has attracted great attention because it can greatly save storage resources and find representative features of data in a low-dimensional space. As a result, it may be widely applied in engineering domains including feature extr

Externí odkaz: http://arxiv.org/abs/2211.04166

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Adversarial Defense via Neural Oscillation inspired Gradient Masking

Autor: Jiang, Chunming, Zhang, Yilei

Spiking neural networks (SNNs) attract great attention due to their low power consumption, low latency, and biological plausibility. As they are widely deployed in neuromorphic devices for low-power brain-inspired computing, security issues become in

Externí odkaz: http://arxiv.org/abs/2211.02223

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