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You can use CNN on any data, but its recommended to use CNN only on data that have spatial features (It might still work on data that doesnt have spatial features, see DuttaAs c^May 13, 2019 · A CNN will learn to recognize patterns across space while RNN is useful for solving temporal data problems. CNNs have become the go-to method for solving any image _Mar 8, 2018 · 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 &Dec 30, 2018 · 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 m#Why would "CNN-LSTM" be another name for RNN, when it doesnt even have RNN in it? Can you clarify this? What is your knowledge of RNNs and CNNs? Do you know what an LSTM is?@Sep 12, 2020 · 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 f-Jun 12, 2020 · Fully convolution networks A fully convolution network (FCN) is a neural network that only performs convolution (and subsampling or upsampling) operations. Equivale