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Juyu Xiao

3 accepted papers

2023

Training Robust Spiking Neural Networks on Neuromorphic Data with Spatiotemporal Fragments

ICASSP 2023accepted

Neuromorphic vision sensors (event cameras) are inherently suitable for spiking neural networks (SNNs) and provide novel neuromorphic vision data for this biomimetic model. Due to the spatiotemporal characteristics, novel data augmentations are required to process the unconventional visual signals o…

Cited by 0SourceScholar
2023

Training Robust Spiking Neural Networks with Viewpoint Transform and Spatiotemporal Stretching

ICASSP 2023accepted

Neuromorphic vision sensors (event cameras) simulate biological visual perception systems and have the advantages of high temporal resolution, less data redundancy, low power consumption, and large dynamic range. Since both events and spikes are modeled from neural signals, event cameras are inheren…

Cited by 0SourceScholar
2023

Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neurons

ICASSP 2023accepted

As the third generation of neural networks, spiking neural networks (SNNs) are dedicated to exploring more insightful neural mechanisms to achieve near-biological intelligence. Intuitively, biomimetic mechanisms are crucial to understanding and improving SNNs. For example, the associative long-term…

Cited by 0SourceScholar