An optical neural network is a physical implementation of an artificial neural network with optical components. Early optical neural networks used a photorefractive...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation...

physical neural network is a type of artificial neural network in which an electrically adjustable material is used to emulate the function of a neural synapse...

seventeenth letter of the Ogham alphabet Optical neural network Onion News Network ONN (radio), the Ohio News Network Onn., a consumer electronics brand that...

A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep...

types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate...

As in other neural networks, their normal use is as software, but they have also been implemented in hardware using FPGAs and by optical implementation...

Quandela [fr], and TundraSystems Global. Linear optical quantum computing Optical interconnect Optical neural network Photonic crystal § Applications Photonic...

subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation...

learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference...

Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by biological neural circuitry...

Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational...

Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the...

words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical...

on-chip wavefront shaping, structured-light generations, and optical neural networks. The meta-structures can also be further integrated with van der...

physicist. He studies quantum information theory, nonlinear optics, optical neural networks, and reservoir computing. Serge Massar was born in Zambia in 1970...

represents a scene as a radiance field parametrized by a deep neural network (DNN). The network predicts a volume density and view-dependent emitted radiance...

have been applied to optical flow and have gained prominence. Initially, these approaches were based on Convolutional Neural Networks arranged in a U-Net...

An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer (with typically...

Engineers (IEEE) Neural Networks Council (now the IEEE Computational Intelligence Society). He is a Fellow of the IEEE and the Optical Society of America...

California Institute of Technology. Her doctoral dissertation, Optical neural networks using volume holograms, was supervised by Demetri Psaltis. Gu was...

document search. Earlier research was concerned with recurrent neural networks and optical computing. His research interests are in intelligent web and...

another image. NST algorithms are characterized by their use of deep neural networks for the sake of image transformation. Common uses for NST are the creation...

advances that can be used to study neural networks (Cullen & Pfister 2011). Optical neural interfaces involve optical recordings and optogenetics, making...

other applications. In 2024, Shastri and his team developed an optical neural network (ONN) that isolates specific transmissions and identifies signals...

Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing...

Kyuma, Variable-sensitivity photodetector of pn-np structure for optical neural networks, Japanese Journal of Applied Physics, Part 2 (Letters), Vol. 33...

neural network. In 1993, Black and Jepson used mixture models to represent optical flow fields with multiple motions (also called "layered" optical flow)...

He is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNNs). He is also one of the main...