The remarkable success of Vision Transformers in Artificial Neural Networks (ANNs) has led
to a growing interest in incorporating the self-attention mechanism and transformer-based …

Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has
garnered widespread academic interest for its intrinsic ability to transmit information in a …

Spiking neural networks (SNNs) have received widespread attention as an ultra-low energy
computing paradigm. Recent studies have focused on improving the feature extraction …

Spiking neural networks (SNNs) are generating wide attention due to their brain-like
simulation capabilities and low energy consumption. Converting artificial neural networks …

The Spiking Neural Network (SNN) is a biologically inspired neural network infrastructure
that has recently garnered significant attention. It utilizes binary spike activations to transmit …

Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-
temporal features. Point clouds are sparse 3D spatial data, which suggests that SNNs …

Brain-like hardware is a key step in realizing artificial intelligent machines, and forgetting
memristor is a new type of memristor whose dynamics are very suitable for simulating …