The growing interest in Artificial Intelligence is pervading several domains of technology and
robotics research. Only recently has the space community started to investigate deep …

Memristive arrays are a natural fit to implement spiking neural network (SNN) acceleration.
Representing information as digital spiking events can improve noise margins and tolerance …

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …

Brain-inspired spiking neural networks (SNNs) are becoming a promising energy-efficient
alternative to traditional artificial neural networks (ANNs). However, the performance gap …

Circularly polarized light (CPL) adds a unique dimension to optical information processing
and communication. Integrating CPL sensitivity with light learning and memory in a photonic …

As the size of large language models continue to scale, so does the computational
resources required to run it. Spiking Neural Networks (SNNs) have emerged as an energy …

Infrared machine vision system for object perception and recognition is becoming
increasingly important in the Internet of Things era. However, the current system suffers from …

Spiking Neural Networks (SNNs) have recently emerged as an alternative to deep learning
owing to sparse, asynchronous and binary event (or spike) driven processing, that can yield …

The field of Deep Learning (DL) has seen a remarkable series of developments with
increasingly accurate and robust algorithms. However, the increase in performance has …

Electrolyte-gated transistors can function as switching elements, artificial synapses and
memristive systems, and could be used to create compact and powerful neuromorphic …