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Hybrid neural network

Hybrid neural network

A network composed of different neural networks for improved performance and accuracy

Hybrid neural network is a network with a combination of different artificial neural networks and approaches. It utilizes features of varying neural networks and approaches to achieve optimum results.

TreNet is a hybrid neural network used for trend prediction. It is composed of a long short term memory recurrent neural network (LSTM RNN) to capture dependency in historical trends, a convolutional neural network (CNN) to extract local features from local raw data and a feature fusion layer to merge and maximize features drawn from LSTM RNN and CNN.

Timeline

May 3, 2019
A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots

Further Resources

Title
Author
Link
Type
Date

A Hybrid Neural Network-Latent Topic Model

Li Wan, Leo Zhu and Rob Fergus

Academic paper

Hybrid Neural Networks for Learning the Trend in Time Series

Tao Lin, Tian Guo and Karl Aberer

Academic paper

Logical Learning Through a Hybrid Neural Network with Auxiliary Inputs

Fang Wan, Chaoyang Song

Academic paper

References

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