Rethinking Pretraining as a Bridge from ANNs to SNNs

1 code implementation • 2 Mar 2022 • Yihan Lin, Yifan Hu, Shijie Ma, Guoqi Li, Dongjie Yu

In this work, a new SNN training paradigm is proposed by combining the concepts of the two different training methods with the help of the pretrain technique and BP-based deep SNN training mechanism.

ES-ImageNet: A Million Event-Stream Classification Dataset for Spiking Neural Networks

1 code implementation • 23 Oct 2021 • Yihan Lin, Wei Ding, Shaohua Qiang, Lei Deng, Guoqi Li

With event-driven algorithms, especially the spiking neural networks (SNNs), achieving continuous improvement in neuromorphic vision processing, a more challenging event-stream-dataset is urgently needed.

Temporal-wise Attention Spiking Neural Networks for Event Streams Classification

no code implementations • ICCV 2021 • Man Yao, Huanhuan Gao, Guangshe Zhao, Dingheng Wang, Yihan Lin, ZhaoXu Yang, Guoqi Li

However, when aggregating individual events into frames with a new higher temporal resolution, existing SNN models do not attach importance to that the serial frames have different signal-to-noise ratios since event streams are sparse and non-uniform.

Audio Classification Gesture Recognition +1

LIAF-Net: Leaky Integrate and Analog Fire Network for Lightweight and Efficient Spatiotemporal Information Processing

no code implementations • 12 Nov 2020 • Zhenzhi Wu, Hehui Zhang, Yihan Lin, Guoqi Li, Meng Wang, Ye Tang

To address this issue, in this work, we propose a Leaky Integrate and Analog Fire (LIAF) neuron model, so that analog values can be transmitted among neurons, and a deep network termed as LIAF-Net is built on it for efficient spatiotemporal processing.

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