Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ ...

The elective core modules cover basics of neuroscience. These are divided into three categories: systems neuroscience, neural computation and theoretical neurosciences, and neurotechnologies and ...

Liquid neural networks are inspired by biological neurons to implement algorithms that remain adaptable even after training. [Hasani] demonstrates a machine vision system that steers a car to ...

In the domain of neural computation, Spiking Neural Networks (SNNs) are distinguished by their unique, biologically informed ...

On Thursday, a large group of university and private industry researchers unveiled Genesis, a new open source computer ...

Tohoku University scientists created lab-grown neural networks using microfluidic devices, mimicking natural brain activity ...

A fully self-training, neural network-based thrust vector control (TVC) system that promises smarter and more efficient ...

Artificial Neural Networks (ANNs) are commonly used for machine vision purposes, where they are tasked with object recognition. This is accomplished by taking a multi-layer network and using a ...

Traditional space-diffractive neural networks suffer from low-space transmission ... on-chip integration and intelligent ...

By merging concepts from neural network theory with protein engineering, "perceptein" represents a biological system capable of performing classification computations at the protein level ...