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The concept of CNN itself is that you want to learn features from the spatial domain of the image which is XY dimension. So, you cannot change dimensions like you mentioned.
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What is the difference between a convolutional neural network and a
A convolutional neural network (CNN) is a neural network where one or more of the layers employs a convolution as the function applied to the output of the previous layer.
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Los estereotipos de género están muy trasnochados y son una realidad contra la que luchar ¿qué os parecen los pictogramas que nos hemos currado?
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How to use CNN for making predictions on non-image data?
You can use CNN on any data, but it''s recommended to use CNN only on data that have spatial features (It might still work on data that doesn''t have spatial features, see DuttaA''s comment below). For
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machine learning
Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations. Equivalently, an FCN is a CNN
Extract features with CNN and pass as sequence to RNN
But if you have separate CNN to extract features, you can extract features for last 5 frames and then pass these features to RNN. And then you do CNN part for 6th frame and you pass
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What is the difference between CNN-LSTM and RNN?
Why would "CNN-LSTM" be another name for RNN, when it doesn''t even have RNN in it? Can you clarify this? What is your knowledge of RNNs and CNNs? Do you know what an LSTM is?