Attention mechanism-based (Attn) temporal convolutional networks (TCN) connected with recurrent neural network (RNN) models for landslide risk prediction are proposed, including TCN-Attn-RNN and ...

This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI.

The time-series data is a type of sequential data and encoder-decoder models are very good with the sequential data and the reason behind this capability is the LSTM or RNN layer in the network.

Recurrent Neural Network models process sequences directly, which are widely used in payload anomaly detection. However, due to the gradient vanishing problem, RNN has limits on processing the long ...

Editor’s note: One of the central technologies of artificial intelligence is neural networks. In this interview, Tam Nguyen, a professor of computer science at the University of Dayton, explains how ...