The past decade has witnessed the great success of deep neural networks in various
domains. However, deep neural networks are very resource-intensive in terms of energy …

As deep learning models scale, they become increasingly competitive from domains
spanning from computer vision to natural language processing; however, this happens at …

Prostate cancer is one of the most common malignant tumors in men. Magnetic resonance
imaging (MRI) has evolved to an important tool for the diagnosis of prostate cancer …

Spiking neural networks (SNNs) are promising alternatives to artificial neural networks
(ANNs) since they are more realistic brain-inspired computing models. SNNs have sparse …

Spiking Neural Networks (SNNs) is promising to enable low power and high performance
edge computing hardware design and have recently attracted attentions of researchers …

Spiking neural networks (SNNs), as the brain-inspired neural networks, encode information
in spatio-temporal dynamics. They have the potential to serve as low-power alternatives to …

The theoretical unbounded orbital angular momentum (OAM) states can be exploited as
data bits in the OAM shift keying (OAM-SK) free-space optical (FSO) communications. In …

Event-based cameras are bio-inspired novel sensors that asynchronously record changes in
illumination in the form of events. This principle results in significant advantages over …

Video analysis is a computer vision task that is useful for many applications like surveillance,
human-machine interaction, and autonomous vehicles. Deep Convolutional Neural …

Spiking Neural Networks (SNNs) have emerged as a promising third generation of neural
networks, offering unique characteristics such as binary outputs, high sparsity, and …