CNN Long Short-Term Memory Networks

Last Updated on August 14, 2019

Gentle introduction to CNN LSTM recurrent neural networks
with example Python code.

Input with spatial structure, like images, cannot be modeled easily with the standard Vanilla LSTM.

The CNN Long Short-Term Memory Network or CNN LSTM for short is an LSTM architecture specifically designed for sequence prediction problems with spatial inputs, like images or videos.

In this post, you will discover the CNN LSTM architecture for sequence prediction.

After completing this post, you will know:

• About the development of the CNN LSTM model architecture for sequence prediction.
• Examples of the types of problems to which the CNN LSTM model is suited.
• How to implement the CNN LSTM architecture in Python with Keras.

Kick-start your project with my new book Long Short-Term Memory Networks With Python, including step-by-step tutorials and the Python source code files for all examples.

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CNN LSTM Architecture

The CNN LSTM architecture involves using Convolutional
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