How do I handle large images when training a CNN?
Suppose that I have 10K images of sizes $2400 times 2400$ to train a CNN. How do I handle such large image sizes without downsampling? Here are a few more specific questions. Are
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machine learning
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 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?
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neural networks
A convolutional neural network (CNN) that does not have fully connected layers is called a fully convolutional network (FCN). See this answer for more info. An example of an FCN is the u-net,
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