55 citations · 59 across the 4 of their papers we have counts for
6 papers
Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks
Guobin Shen, Dongcheng Zhao, Yi Zeng
The spiking neural network (SNN) mimics the information processing operation in the human brain, represents and transmits information in spike trains containing wealthy spatial and…
BackEISNN: A Deep Spiking Neural Network with Adaptive Self-Feedback and Balanced Excitatory-Inhibitory Neurons
Dongcheng Zhao, Yi Zeng, Yang Li
Spiking neural networks (SNNs) transmit information through discrete spikes, which performs well in processing spatial-temporal information. Due to the non-differentiable character…
BSNN: Towards Faster and Better Conversion of Artificial Neural Networks to Spiking Neural Networks with Bistable Neurons
Yang Li, Yi Zeng, Dongcheng Zhao
The spiking neural network (SNN) computes and communicates information through discrete binary events. It is considered more biologically plausible and more energy-efficient than a…
Responsible Facial Recognition and Beyond
Yi Zeng, Enmeng Lu, Yinqian Sun +1
Facial recognition is changing the way we live in and interact with our society. Here we discuss the two sides of facial recognition, summarizing potential risks and current concer…
FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition
Hongyin Zhu, Wenpeng Hu, Yi Zeng
Named entity recognition (NER) is a foundational technology for information extraction. This paper presents a flexible NER framework compatible with different languages and domains…
Linking Artificial Intelligence Principles
Yi Zeng, Enmeng Lu, Cunqing Huangfu
Artificial Intelligence principles define social and ethical considerations to develop future AI. They come from research institutes, government organizations and industries. All v…