The spiking neural network (SNN), as a promising brain-inspired computational model with
binary spike information transmission mechanism, rich spatially-temporal dynamics, and …

Spiking neural networks (SNNs) are brain-inspired energy-efficient models that encode
information in spatiotemporal dynamics. Recently, deep SNNs trained directly have shown …

Spiking neural network (SNN) is a new generation of artificial neural networks (ANNs),
which is more analogous with the brain. It has been widely considered with neural …

Spiking neural network (SNN) has been viewed as a potential candidate for the next
generation of artificial intelligence with appealing characteristics such as sparse …

Wide-scale use of visual surveillance in public spaces puts individual privacy at stake while
increasing resource consumption (energy, bandwidth, and computation). Neuromorphic …

Recently, some researchers have begun to adopt the Transformer to combine or replace the
widely used ResNet as their new backbone network. As the Transformer captures the long …

Spiking neural networks (SNNs) have shown much promise as an energy-efficient
alternative to artificial neural networks (ANNs). Such methods trained by surrogate gradient …

Human speech perception is intrinsically a multi-modal task since speech production
requires the speaker to move the lips, producing visual cues in addition to auditory …

The polarization event camera PDAVIS is a novel bio-inspired neuromorphic vision sensor
that reports both conventional polarization frames and asynchronous, continuously per-pixel …

Sign language recognition has been utilized in human–machine interactions, improving the
lives of people with speech impairments or who rely on nonverbal instructions. Thanks to its …