How can pass the output of the fully connected layer of a deep learning model to the sequence input layer of another deep learning model?

I need to known how to pass the features extracted from the fully connected layers of a pre-trained model for example (Alexnet) to

a sequence input layer of an LSTM model any Help.

[mahmoud Bassiouni]

So that the Alexnet and the LSTM model become one model

Answer 1

[James Gross]

Hi Mahmoud,

Considering the sequence input layer and LSTMs are meant to be used for sequential data while AlexNet is for images, it sounds like you would like to use a pre-trained image classification model for video classification. If this is the case, the following documention example demonstrates precisely how to do this using GoogleNet.

https://www.mathworks.com/help/deeplearning/ug/classify-videos-using-deep-learning.html

You should be able to easily modify this example for a pre-trained image classification model of your choosing.

I hope this information helps!

James