Results 251 to 260 of about 176,660 (282)
Some of the next articles are maybe not open access.
Recurrent Neural Networks (RNNs)
2019Recurrent neural networks (RNNs) are another specialized scheme of neural network architectures. RNNs are developed to solve learning problems where information about the past (i.e., past instants/events) is directly linked to making future predictions. Such sequential examples play up frequently in many real-world tasks such as language modeling where
openaire +1 more source
RNN-LSTM-Based Model Predictive Control for a Corn-to-Sugar Process
Processes, 2023Chengbo Li, Lei Zhang, Yachao Dong
exaly
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
IEEE Transactions on Image Processing, 2020Pengfei Zhang, Jian-Ru Xue, Cuiling Lan
exaly
What is the best RNN-cell structure to forecast each time series behavior?
Expert Systems With Applications, 2023Rohaifa Khaldi +2 more
exaly
RECURRENT NEURAL NETWORKS (RNNS)
Recurrent Neural Networks (RNNs) are a specialized class of neural networks designed to process sequential data. Unlike traditional feedforward networks, RNNs utilize internal memory to maintain contextual information across time steps, making them ideal for tasks such as language modeling, time series forecasting, and speech recognition.Waseem Ahmad, Vishal Goyal, Dr. Surender
openaire +1 more source