… overview of artificial neural network. The artificial neural network learns by updating the
network architecture and connection weights so that the network can efficiently perform a task. It …

… for deep convolutional neural networks and self-attention based networks such as the …
a timely overview of both old and current compression techniques for deep neural networks, …

… “neural network” bring a hopeful vision to scientists and engineers who anticipate synthesis
of … The neural network exemplifies the paradox that the enthusiasm of ardent advocates can …

… An Artificial Neural Network is a computational model inspired in the functioning of the …
depend on weights of the neural network. As The word network in Neural Network refers to the …

… , generalized neural networks resulting from the integration of multilayer neural networks …
in the very early stages, generalized neural networks appear to be an attractive compromise …

… on biological neural network gives birth to an artificial neural network (ANN)… neural networks
and follow with an overview of ANN. Finally, we review several examples of neural networks…

… neural networks submitted their most recent results concerning their research in neural networks
… as a list of sources of information concerning neural networks, such as journals, books, …

… of neural networks in problems of structural analysis and design. The present paper provides
an overview … Such applications have included, among others, the use of neural networks in …

… In this paper, we have reviewed the fundamental architecture of the convolutional neural
network. … Finally, we have described several applications of the convolutional neural network. …

Convolutional neural network (CNN), a class of artificial neural networks that has become
dominant in various computer vision tasks, is attracting interest across a variety of domains, …