Understanding the Effective Receptive Field in Deep Convolutional Neural Networks

How do you (in simple theory) calculate the receptive input field of a certain cell in a feature map in a convolutional neural network?


Counting backwards from the feature layer to the input layer, each layer increases the receptive field size by the kernel size.

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