American Institute of Physics

Hybrid convolutional neural network yields energy-efficient approach with analog first layer

Oscillatory retinal neuron networks don’t require external voltage sources and show comparable performance to cutting-edge GPU-based convolutional neural networks, for energy costs thousands of times ...
Nature

All-optical convolutional neural network based on phase change materials in silicon photonics platform

This paper presents a design for an integrated all-optical convolution neural network in which all three network layers i.e. convolution, max-pooling and fully connected can be implemented in silicon ...
Nature

Convolutional spiking neural networks for intent detection based on anticipatory brain potentials using electroencephalogram

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for ...
Geeky Gadgets

What is an AI neural network and how do they work?

AI neural networks, inspired by the human brain are a foundational technology in the field of artificial intelligence. They are designed to recognize patterns and make decisions with a level of ...