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(hidden layers). A network is typically called a deep neural network if it has at least two hidden layers. Artificial neural networks are used for various...

Biological neural networks are studied to understand the organization and functioning of nervous systems. Closely related are artificial neural networks, machine...

processing, brain–computer interfaces, and financial time series. CNNs are also known as shift invariant or space invariant artificial neural networks, based on...

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

function for deep neural networks. Rectified linear units find applications in computer vision and speech recognition using deep neural nets and computational...

recurrent neural networks and convolutional neural networks, renewed interest in ANNs. The 2010s, saw the development of a deep neural network (a neural network...

architectures such as deep neural networks, deep belief networks, recurrent neural networks, convolutional neural networks and transformers have been...

Spiking neural networks (SNNs) are artificial neural networks (ANN) that more closely mimic natural neural networks. In addition to neuronal and synaptic...

in neural networks that are otherwise unrelated to ResNet. The residual connection stabilizes the training and convergence of deep neural networks with...

Recurrent neural networks (RNNs) are a class of artificial neural networks for sequential data processing. Unlike feedforward neural networks, which process...

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

or loops, in contrast to recurrent neural networks, which have a bi-directional flow. Modern feedforward networks are trained using the backpropagation...

intelligence and machine learning applications, including artificial neural networks and computer vision. Typical applications include algorithms for robotics...

In artificial intelligence, a differentiable neural computer (DNC) is a memory augmented neural network architecture (MANN), which is typically (but not...

doi:10.1016/0893-6080(90)90049-Q. "Probabilistic Neural Networks :: Radial Basis Networks (Neural Network Toolbox™)". www.mathworks.in. Archived from the...

A Siamese neural network (sometimes called a twin neural network) is an artificial neural network that uses the same weights while working in tandem on...

An optical neural network (ONN) is a physical implementation of an artificial neural network with optical components. Early ONNs used a photorefractive...

matching capabilities of neural networks with the algorithmic power of programmable computers. An NTM has a neural network controller coupled to external...

In computer science and machine learning, cellular neural networks (CNN) or cellular nonlinear networks (CNN) are a parallel computing paradigm similar...

Neural Networks is a monthly peer-reviewed scientific journal and an official journal of the International Neural Network Society, European Neural Network...